Trusted AI Challenge: Rules

The Amazon Trusted AI Challenge (the “Competition”) is a university competition sponsored by Amazon.com Services LLC (“Sponsor”), in which teams of college or university students compete to accelerate advances in artificial intelligence (AI). This year’s Competition will task student teams competing against each other with the goal of making AI safer for all, with a focus on preventing AI from assisting with writing malicious code or writing code with security vulnerabilities. University teams will focus on building security features and enhancing the robustness of code-generating models. Each team will focus on either building security features for code-generating models (i.e., defense models), or dynamic red-teaming techniques to help test these models (i.e., red-teaming systems).

Selected teams will have the opportunity to participate in the Competition, and final results will be announced in July 2025. See below for the Competition details.

By applying to or participating in the Competition, you agree to these Official Rules. Please read them carefully.

COMPETITION CALENDAR
Applications to participate in the Competition can be submitted starting July 8, 2024. After participating teams are selected, the Competition will run from November 2024 through July 2025 (the "Competition Period"). The Competition phases are noted in the calendar below. The dates are approximate and are subject to change at Sponsor’s discretion.

PhasesStarts on
Phase 1: Participant Application Period7/8/2024
Phase 2: Sponsor Application Review Period9/2/2024
Phase 3: Participant Notification Period and Onboarding9/16/2024
Bootcamp11/18/2024
Phase 4: Initial Build Period11/21/2024
Phase 5: Tournament PeriodJanuary 2025
Phase 6: Finals EventJune 2025
Winners AnnouncedJuly 2025

COMPETITION OVERVIEW
University teams will focus on maintaining the benefits and utility of code generation models, while improving their robustness with respect to security principles. During the Competition, each team will focus on either building security features into a code-generating model (i.e., model developer teams), or developing dynamic automatic red-teaming techniques (i.e., red teams). For applications, each team may choose to apply for either a red-team role or model developer teams role, or they may choose to apply for either role and be assigned a role in Sponsor’s discretion. Throughout the Competition, red teams and model developer teams will participate in tournaments where automatic red teaming systems have the opportunity to identify weaknesses in model developer teams’ models - providing teams with feedback from dynamic, multi-turn interactions.

ELIGIBILITY
To be eligible to participate in the Competition, you must: (1) be enrolled as a full-time undergraduate or post-graduate student at an accredited college or university (other than colleges or universities located in any of the Restricted Jurisdictions defined below) (“Universities”) and remain a full-time student in good standing at such University while participating in the Competition; (2) be at or above the age of majority in your country, state, province or jurisdiction of residence at the time of entry; and (3) not be a person or entity subject to U.S. export controls or sanctions, including citizens of any of the Restricted Jurisdictions defined below. Competition is void in Cuba, Iran, Syria, North Korea, Sudan, the region of Crimea, the so-called Donetsk People’s Republic (DNR) or Luhansk People’s Republic (LNR), and where prohibited by law (each, a “Restricted Jurisdiction”). People who, during the Competition Period, are directors, officers, employees, interns, and contractors (“Personnel”) of Sponsor, its parents, subsidiaries, affiliates, and their respective advertising, promotion and public relations agencies, representatives, and agents (collectively, “Competition Entities”), immediate families members of such Personnel (parents, siblings, children, spouses, and life partners of each) and members of the households of such Personnel (whether related or not) are ineligible to participate in this Competition. Sponsor reserves the right to verify eligibility and to adjudicate on any dispute at any time.

Entrants (“Entrants”) must enter as part of an “Entrant Team” consisting of one or more students from a single University. An Entrant is only permitted to be part of one Entrant Team. Any Entrant that is part of more than one Entrant Team may be disqualified and his/her corresponding Entrant Teams may be disqualified at the sole discretion of Sponsor. Only one member of the Entrant Team may submit an application on behalf of an Entrant Team but all those listed on the application are Entrants. All prize money payable to Entrant Teams will be split evenly among eligible Entrants of a winning Entrant Team (based on the pre-tax amount of prize money), as identified in the application, as updated as permitted by these Official Rules, and who maintain full-time student status in good standing at their University during the entire Competition Period.

Each team must select a faculty advisor, who, with respect to that team, will act as the official representative for the Entrant Team’s University (the “Faculty Advisor”). Each Entrant Team must have its own Faculty Advisor; Faculty Advisors may not represent multiple teams. Faculty Advisors are not members of the Entrant Team and will not receive any portion of any prize. Faculty Advisors must remain full time employees of the Entrant Team University during the entire Competition Period. During the Competition Period, but no later than April 20, 2025, the Faculty Advisor may request to remove members from the Entrant Team or to add additional members to the Entrant Team. The Faculty Advisor must provide an explanation of the reason for the removal or addition, and any proposed new member must provide documentation requested by Sponsor and agree to comply with these Official Rules. Changes to the Entrant Team are subject to Sponsor’s approval in its sole discretion. If at any point during the Competition Period, the Entrant Team’s Faculty Advisor cannot continue to serve as a Faculty Advisor, the Entrant Team may submit a request to Sponsor to select a new Faculty Advisor. Changes to the Entrant Team’s Faculty Advisor are subject to Sponsor’s approval in its sole discretion. If an Entrant Team fails to have a Faculty Advisor at any point in time during the Competition, for any reason, the Entrant Team may be disqualified.

Each Entrant must be eligible to participate in this Competition and comply with these Official Rules or the Entrant, and the Entrant Team associated with that Entrant, may be disqualified. This Competition is subject to all applicable federal, state, territorial, provincial, and local laws. Competition is void where prohibited. By participating in the Competition, all Entrants accept and agree to comply with and abide by these Official Rules and the decisions of the Sponsor which will be final and binding, including the Sponsor’s right to verify eligibility, to interpret these Official Rules, and to resolve any disputes relating to this Competition at any time. Only Entrants may work on the Competition or their entries (e.g., models or red-teaming systems), although employees of the Sponsor may provide support to the Entrant Team during the Competition Period, and the Faculty Advisor, and other students and faculty members at an Entrant Team’s University may provide support and advice to the Entrant Team and may co-author the Technical Article (as defined below) or other research papers.

ADDITIONAL REQUIREMENTS
During all phases of the Competition, Sponsor may in its sole discretion require Entrant Teams to provide periodic status updates, reports, or demonstrations of the red-teaming system or model. Sponsor may also require Entrant Teams to comply with additional rules, requirements, or procedures that Sponsor determines, in its sole discretion, are necessary for the administration of the Competition. Sponsor may in its sole discretion penalize teams for noncompliance with any rules, requirements, or procedures, including by disqualification from the Competition.

Sponsor may provide Entrants selected to participate in the Competition access to generative AI models, software, software development kits, libraries, APIs, documentation, sample code, data sets, and related materials (“Program Materials ” and “Restricted Program Materials”) that may be used in connection with the Competition. If an Entrant uses any Program Materials or Restricted Program Materials, the Entrant is subject to and agrees to comply with Sponsor’s Program Materials License Agreement or a substantially similar alternative license that may be applied at Sponsor’s sole discretion. Program Materials and Restricted Program Materials may include APIs, data sets, models, model outputs, and other materials that are not public (“Non-Public Materials”).

Each Entrant and Faculty Advisor agrees that they will not disclose, distribute, or otherwise make available any Non-Public Materials to anyone other than other Entrants of their Entrant Team and the Entrant Team’s Faculty Advisor. Each Entrant (and each Faculty Advisor) agrees that they will use Non-Public Materials only in connection with the development of a model or red-teaming system as part of the Competition and in compliance with these Official Rules. Entrants (and Faculty Advisors) may not use Non-Public Materials for any other purpose. Entrants (and Faculty Advisors) must return or destroy all Non-Public Materials (in any form and including, without limitation, all summaries, copies and excerpts of the same) promptly following any request from Sponsor, or if the Entrant Team discontinues the development or operation of its model or red-teaming system. If any Entrant or Faculty Advisor is disqualified from the Competition, leaves the University, or otherwise terminates their participation in the Competition, that individual must immediately return or destroy all Non-Public Materials in their possession. Sponsor reserves the right in its sole discretion to impose additional terms and conditions on the use of Program Materials, and to condition access to Program Materials on Entrants’ agreement to those terms and conditions.

Each Entrant Team and Faculty Advisor agrees that they will not copy, disclose, distribute, or otherwise use any output created by a generative AI model during the course of this competition for any purpose other than the development or improvement of their systems as part of this Competition. Entrant Teams may not publish any model output or publish or deploy their systems for any purpose, including in connection with any paper submission, without prior review and approval by Sponsor.

DESCRIPTION OF COMPETITION PHASES
PHASE 1 “Participant Application Period”: Between July 8, 2024 and September 1, 2024, the student leader of each Entrant Team that wishes to enter the Competition may visit amazon.science/trusted-ai-challenge (the “Competition Site”) to submit their entry information via the YouNoodle, Inc. (“YouNoodle”) application portal, including but not limited to: complete names, contact information, and resumes of all Entrant Team members, proof of University enrolled status (e.g., verification of enrollment or an uploaded copy of Entrants’ student IDs), name and contact information of a sponsoring Faculty Advisor from the Entrant Team’s University, and a bio for each Entrant Team member.

Sponsor will consider applications by multiple different teams from a single institution, but each Entrant Team must have their own Faculty Advisor, and there can be no overlap in the composition of the Entrant Teams or Faculty Advisors. If more than one Entrant Team is accepted from any university, the Teams will be expected to work independently, and any collaboration or coordination among Entrant Teams will be grounds for disqualification.

Entry Applications may be submitted at any time during the Participant Application Period. Only one individual per Entrant Team may submit an Entry Application on behalf of their Entrant Team. Other members of the Entrant Team must accept the invitation to join the team via the YouNoodle application portal. All Entrants must create an account with YouNoodle if they have not done so already in order to submit an Entry Application or accept an invitation to join an Entrant Team and participate in the Competition. Creating and maintaining a YouNoodle account is free of charge. All Entry Applications must be complete when the Participant Application Period closes at 11:59 pm Pacific Time on the last day of the Participant Application Period. Entry Applications are not complete until all the online prompts and instructions to upload the Entry Application have been properly followed, the Official Rules have been accepted, and all Entrant Team members and the Faculty Advisor have accepted their invitations to join the Entrant Team via the YouNoodle application portal. Entry Applications may not be revised once submitted. Once submitted, Entry Applications will not be returned and become the property of the Sponsor.

Entry Terms: Determination of eligibility and compliance with these Official Rules and any other requirements imposed by Sponsor will be in the sole discretion of the Sponsor. By entering, Entrants represent that all information and materials submitted to Sponsor in connection with the Competition:

  1. are the original work of the Entrant Team or an update to an original work of the Entrant Team;
  2. do not infringe or violate the rights of any third party, including but not limited to copyrights, trademarks or copyrighted material not owned by the Entrant Team, contract and licensing rights, rights of publicity or privacy, moral rights, or any other intellectual property rights; and
  3. are not subject to any third-party agreements, and that Sponsor will not be required to pay or incur any sums to any person or entity as a result of its exercise of any rights granted under these Official Rules.

As referenced above, each Entrant Team will be required to apply for at least one role (i.e., either the red-team role or model developer role). Alternatively, Entrant Teams can choose to apply for both roles and Sponsor will assign one of the two roles to a team based on the Entry Application in its sole discretion.
PHASE 2 “Sponsor Application Review Period”: All eligible Entry Applications will be reviewed by the Sponsor. Sponsor will select up to ten (10) Entrant Teams for the Competition in its sole discretion, based on the following criteria:

  • The potential scientific contribution to the field;
  • The technical merit of the approach;
  • The novelty of the idea; and
  • An assessment of the Entrant Team’s ability to execute against their plan.

PHASE 3“Participant Notification Period”: Entrant Teams selected by Sponsor to participate in the Competition will be notified by email at the email address provided at time of Entry Application. Entrant Teams acknowledge that some Entrant Teams may include Entrants and Faculty Advisors who participated in prior competitions and other promotions offered by Sponsor.

Stipends: Each Entrant Team selected to participate in the Initial Build Period will be eligible to receive a restricted research grant of $250,000 U.S. dollars (paid in any number of installments as determined by Sponsor in its sole discretion, subject to Entrant Team’s continued participation in and eligibility for the Competition), which will be paid to the Universities of the selected Entrant Teams in the form of restricted research grants. These grants will be awarded to the Universities and not the Entrant Teams or any individual Entrant, and will be subject to the University signing and returning any agreements or other documents required by Sponsor (including IRS forms W-9 and/or W-8), and to the University agreeing in writing that no more than 35% of the research grants may be allocated to administrative fees. Entrant Teams will not be eligible to begin participating in the Competition until all required agreements and other documentation have been completed by the University. The grants are intended to support two full-time students or the equivalent of two full-time students during the Competition and one month of the Faculty Advisor’s salary. Each University will be responsible for allocating and managing the funds within these guidelines and for payment and reporting of any required taxes, withholdings, fees, or duties. Sponsor is not responsible for managing the funds, including their allocation or distribution by the University, after they are paid to the University. Each member of an Entrant Team whose University receives a stipend award, and its Faculty Advisor, will also receive free AWS services to support the development of their model or red-teaming system (subject to reasonable limitations set by Sponsor), and support from the Sponsor as determined by Sponsor.

Stipends are non-transferable except as directed by Sponsor. No stipend substitutions or cash redemptions are allowed except as designated by Sponsor. Except where prohibited by law, all federal, state, provincial, or other tax liabilities or withholdings are the responsibility of the University and the Sponsor will not be responsible for any tax deductions which may be necessary, except that Sponsor may withhold taxes as required by law. Universities are responsible for any costs and expenses associated with stipend acceptance and use. If an Entrant Team withdraws from the Competition or does not remain compliant with these Official Rules, Sponsor will be relieved of any obligation to pay any remaining portion of the stipend to the Entrant Team’s University. All details relating to the stipend not specified herein shall be determined solely by Sponsor.

Boot Camp: Selected Entrant Teams will be invited to a Competition Boot Camp which Sponsor intends to hold in Fall 2024 at Sponsor’s headquarters in Seattle, Washington or alternative location as determined by Sponsor. Entrant Teams will be expected to book their flight and hotels and cover the travel cost using the awarded stipend. Faculty Advisors and at least 1 student team member are expected to attend the Boot Camp. In the event that Sponsor is unable to hold a Boot Camp, Sponsor may reschedule or cancel the Boot Camp at its sole discretion, and Sponsor is not required to reimburse any expenses incurred by Entrant Teams.

PHASE 4 “Initial Build Period”: Selected Entrant Teams will develop their model or red-teaming system. Sponsor will provide each Entrant Team with certain Program Materials or Restricted Program Materials by the beginning of the Initial Build Period.

PHASE 5 “Tournament Period”: The Tournament Period will comprise of three rounds of tournaments. The exact start date and end date of each of the tournaments will be announced prior to the start of the first tournament. On the start date of each of the three tournaments both red teams and model developer teams will submit their red-teaming system and model, respectively, to the Sponsor. Sponsor will then complete a utility evaluation of the model. At the sole discretion of the Sponsor, models may be allowed multiple attempts to pass the utility evaluation; however, teams that are not able to pass the utility evaluation may be disqualified from the tournament. Following the utility evaluation, both red teams and model developer teams will move on to the tournament where each of the red-teaming systems and models will be matched against each other.

During the tournament, each red-teaming system will try to break each model’s defense by either getting the model to provide assistance with writing malicious code and/or generation of vulnerable code (i.e., a model generates code with security vulnerabilities). The Sponsor will then evaluate the interactions between each match-up. Red teams and model developer teams will be ranked separately. Model developer teams (i.e., owners of models) will be ranked based on their system’s average defense success rate across all red-teaming systems. Red teams (i.e., owners of red-teaming systems) will be ranked based on a combination of their diversity of red-team techniques and their average red-teaming success rate across all models.

No teams will be eliminated during the tournament rounds. Evaluation results may be provided to the Entrant Teams, as determined by Sponsor in its sole discretion. Both red teams and model developer teams may improve their systems in between tournament rounds, after the Sponsor notifies them that a tournament round is complete. Teams may not modify their model or red-teaming system systems while the tournament round is on-going. To move to the Finals Event, teams must meet minimum success criteria that will be established and provided to Entrant Teams during the Tournament Period. Teams that do not meet this criteria at the end of the third tournament may be eliminated following the end of the Tournament Period.

Summit: Sponsor at its sole discretion may choose to hold a summit after the Tournament Period, but before the Finals Event. Sponsor may elect to provide each finalist Entrant Team reimbursement for the cost of airline tickets (non-refundable coach class booked through Sponsor at least 14 days in advance) to the site of the Summit where Entrant teams will present their innovations from the competition, and the provision of hotel rooms at the site of the Summit or such other event, to permit members of each Entrant Team (up to a maximum number of members determined by Sponsor) and the Faculty Advisor to attend the Summit or such other event. Travel expense subsidies and access to the event may be subject to tax information reporting and withholding to the extent required by law.

Disclosure of Third-Party Funding. If any Entrant Team receives any third-party funding to facilitate its participation in this Competition, such funding must be disclosed to Sponsor no later than the last date of the Tournament Period, along with any requirements imposed on the Entrant Team in connection with the funding. Entrant Teams may not accept or use any third-party funding if acceptance or use of that funding, or any requirements imposed in connection with that funding, would conflict with these Official Rules.

Technical Publication: No later than the first day of the 3rd tournament round all participating Entrant Teams must submit to Sponsor a technical article including (a) the technical approach for their model or red-teaming system, and (b) any comparative experiments performed by the Entrant Team and results of those experiments (a “Technical Article”). Entrant Team’s Technical Article must include sufficient detail to permit other researchers to replicate the work. However, Technical Articles may not include any Non-Public Materials or other confidential information of Sponsor or its affiliates. If a Technical Article does not provide sufficient detail to replicate the work, Sponsor may require the Entrant Team to provide Sponsor any additional information needed to replicate the work. Sponsor will publish the Technical Articles in connection with the Finals Event. Prior to the publication, Sponsor will not disclose Technical Articles to third parties. Entrant Teams may update their Technical Articles prior to the Finals Event.

In addition to the required Technical Articles, Entrants may publish other technical articles describing their work (“Additional Articles”). However, prior to submitting any technical articles to any publication, conference, or other venue for publication, Entrant Teams must obtain Sponsor’s written approval. Additional Articles may not include any Non-Public Materials or other confidential information of Sponsor or its affiliates. Entrants must submit any Additional Articles to Sponsor for review and comment at least two weeks prior to the submission deadline and must make, prior to submission, any changes or deletions requested by Sponsor to protect confidential or other sensitive information.

PHASE 6 “Finals Event”: Sponsor will hold a multi-day Finals Event that will be structured as follows. Sponsor will recruit expert red teamers to serve as judges (e.g., cybersecurity experts) that will come onsite to Sponsor’s campus (Entrant Teams will not be onsite during the Finals Event). For both red teams and model developer teams, evaluation of red-teaming or defense success in finals will be by these expert human judges. Red-teaming and model developer teams will be matched up against each other as they were in previous tournaments, with the addition of human expert red teamers having the opportunity to launch red-teaming techniques on each of the model developer finalists. The final ranking and determination of winners for models will combine their defense performance against the finalist red-teaming system and against human red teamers. The final ranking and determination of winners for red-teaming systems will be determined by scoring their red-teaming success by expert human judges.

Winners Announcement Event: Sponsor may elect to provide each finalist Entrant Team reimbursement for the cost of airline tickets (non-refundable coach class booked through Sponsor at least 14 days in advance) to the site of the event announcing the winners of the Competition, and the provision of hotel rooms at the site of the Event or such other event, to permit members of each finalist Entrant Team (up to a maximum number of members determined by Sponsor) and the Faculty Advisor to attend the Event or such other event. Travel expense subsidies and access to the event may be subject to tax information reporting and withholding to the extent required by law.

PHOTO, UNIVERSITY LOGO AND TEAM WRITE-UP REQUIREMENTS
Each selected Entrant Team must provide a team photo including all the team members and faculty advisor within 15 days of selection. No photo collage of individual pictures will be accepted. The team photos must be rectangular or square. Entrant Team photos that are strongly horizontal or vertical will not be accepted. The Entrant Team must provide a 50 word write-up about the each individual team member and faculty advisor also within 15 days of selection. The write-up must be written in the third person. Every subsequent reference to the member must be a pronoun or last name. e.g.,: “Tom Smith is a computer science PhD student at ABC university, he/Smith is studying..” When requested by Sponsor, Entrant Teams must provide a high quality University logo that the Sponsor is free to use for any marketing or promotional content for the Trusted AI Challenge program.

PRIZES
Overall Performance Prize
Following the Finals Event, the two finalist red-teaming systems that attain the two highest ranks among the finalist red-teaming systems and the two finalist models that attains the two highest ranks among the finalist models will be the First-Place and Second-Place winners of the Overall Performance prizes. If there is a tie in the scores for any prize, Sponsor will rank the systems based on their Tournament Period performance. Sponsor’s decisions are final and binding in all matters relating to this Competition, including the determination of prize winners.

First-Place Overall Performance Model (1 winner): The Entrant Team that receives the highest rank for a model will receive $250,000 U.S. dollars divided equally among all members of that Entrant Team.
Second-Place Overall Performance Model (1 winner): The Entrant Team that receives the second highest rank for a model will receive $100,000 U.S. dollars awarded in the form of checks divided equally among all members of that Entrant Team.
First-Place Overall Performance Red-Teaming System (1 winner): The Entrant Team that receives the highest rank for a red-teaming system will receive $250,000 U.S. dollars awarded in the form of checks divided equally among all members of that Entrant Team.
Second-Place Overall Performance Red-Teaming System (1 winner): The Entrant Team that receives the second highest rank for a red-teaming system will receive $100,000 U.S. dollars awarded in the form of checks divided equally among all members of that Entrant Team.

Prize Conditions: Prizes are non-transferable except as directed by Sponsor. No prize substitutions allowed. Except where prohibited by law, all federal, state, provincial, or other tax liabilities are the responsibility of the prize winners, Sponsor will not be responsible for any tax deductions which may be necessary, and Sponsor reserves the right to withhold taxes as required by law. Prize winners will be responsible for paying all costs and expenses related to the prize that are not specifically mentioned, including, but not limited to, taxes, withholdings, and any other expenses that might reasonably be incurred by the winner in receiving or using the prize. All prizes awarded will be subject to any taxes Sponsor is required by law to withhold as well as applicable sales, use, gross receipts, goods and service, or similar transaction-based taxes. IF TAXES ARE APPLICABLE TO THE PRIZE(S), IT IS THE RESPONSIBILITY OF THE WINNER TO PAY TO THE APPROPRIATE AUTHORITIES. PAYMENTS TO COMPETITION WINNERS ARE SUBJECT TO THE EXPRESS REQUIREMENT THAT THE WINNER SUBMIT TO SPONSOR ALL DOCUMENTATION REQUESTED BY SPONSOR (INCLUDING FORMS W-9 OR W-8BEN AS REQUESTED BY SPONSOR) TO PERMIT COMPLIANCE WITH ALL APPLICABLE STATE, FEDERAL, LOCAL AND FOREIGN (INCLUDING PROVINCIAL) TAX REPORTING AND WITHHOLDING REQUIREMENTS. Prize winners are responsible for ensuring that the tax documentation submitted to Sponsor complies with all applicable tax laws and requirements. If a winner fails to provide the documentation or submits incomplete documentation, the prize may be forfeited and Sponsor may, in its sole discretion, select an alternate winner. Sponsor will divide all awards that are payable to any Entrant Team evenly among the Entrant Team members and distribute accordingly. Designation as a prize winner is subject to Entrant’s proof of compliance with these Official Rules, maintaining compliance with these Official Rules and approval by Sponsor. All details of prizes not specified herein shall be determined solely by Sponsor.

PRIVACY: Entrants and Faculty Advisors acknowledge and agree that Sponsor may collect, store, share, and otherwise use personally identifiable information provided during the application process and the Competition, including, but not limited to, name, mailing address, phone number, and email address. All personally identifiable information collected is subject to and will be used in accordance with Sponsor’s Privacy Notice (www.amazon.com/privacy) and YouNoodle’s Privacy Policy (www.younoodle.com/privacy), including for administering the Competition and verifying Entrants’ and Faculty Advisors’ identities, addresses, and telephone numbers in the event an entry qualifies for a prize. YouNoodle’s servers are located in the United States. By participating in this Competition, Entrants and Faculty Advisors authorize the transfer of personal data to the United States for purposes of administering the Competition, conducting publicity about the Competition, and additional purposes consistent with Sponsor’s goals or the Competition goals. By entering the Competition, Entrants and Faculty Advisors consent to Sponsor’s and YouNoodle’s collection, and Sponsor’s use and disclosure of entrants’ personally identifiable information for these purposes. The data controller for information collected by Sponsor is Amazon.com Services LLC, 410 Terry Ave North, Seattle, Washington 98109, USA.

INTELLECTUAL PROPERTY: By entering the Competition, each Entrant and Entrant Team represents and warrants that he or she has obtained all of the rights, licenses, and permissions in writing that are otherwise necessary for the Entrant Team to operate or distribute the model or red-teaming system and to grant to Sponsor the licenses set forth in these Official Rules and in the Developer Agreement. Entrants MAY NOT submit models or red-teaming systems created by any person other than themselves or their Entrant Team members.

As between Sponsor and Entrant Teams, models or red-teaming systems created by Entrant Teams will remain the property of the respective Entrant Teams or their University, excluding any Program Materials or Restricted Program Materials incorporated in the systems, which will remain the property of Sponsor. All output generated by any model or red-teaming system during the course of the Competition will be the property of Sponsor, and Entrant Teams will have limited rights to use the output for the sole purpose of improving or training their modes or systems for the purpose of this Competition. By submitting a model or red-teaming system in this Competition, each Entrant and Entrant Team represents and warrants that they own, or otherwise have the right to use and license, all of the intellectual property and other rights in and to the model or red-teaming system. Each Entrant and Entrant Team hereby grants Sponsor and its affiliates a non-exclusive, perpetual, irrevocable, worldwide, and royalty-free license to make, have made, use, sell, offer for sale, import, export, license, exploit, promote, reproduce, make available, publicly display, publicly perform, create derivative works of, and otherwise exercise all intellectual property and other rights in and to any concepts, works, inventions, information, designs, programs, software, or other materials that the Entrant or Entrant Team develops or submits in connection with the Competition or the creation of the model or red-teaming system, including any of the foregoing included or described in any Technical Article or other materials provided to Sponsor. In addition, upon Sponsor’s request, all Entrants and Entrant Teams must provide Sponsor all source code and algorithms developed in connection with the Competition. Each Entrant agrees to do or perform, or cause to be done and performed, all such further acts and things, and execute and deliver all such other agreements, certificates, instruments, and documents as Sponsor may reasonably request in order to carry out the intent and accomplish the purposes of the foregoing license.

Except where prohibited, each Entrant and Entrant Team further consents (and agrees to sign any additional documents required by Sponsor to formalize, effect, or perfect such consent) to Competition Entities’ model or red-teaming systems pursuant to these Official Rules and the use of any Entrant or Entrant Team names, likeness, biographical information, and voice in advertising, publicity, trade, and other marketing and promotional materials (including video, audio, and print through all means of distribution) worldwide without compensation, notice, or approval, and disclaims any ownership rights to the content of such materials.

Waiver, Release, and Limitation of Liability
EACH ENTRANT ACCEPTS THE CONDITIONS STATED IN THESE OFFICIAL RULES, AGREES TO BE BOUND BY THE DECISIONS OF SPONSOR, WARRANTS THAT THE ENTRANT IS ELIGIBLE TO PARTICIPATE IN THIS COMPETITION, AND AGREES TO RELEASE, INDEMNIFY, AND HOLD HARMLESS THE COMPETITION ENTITIES AND THE PERSONNEL OF EACH FROM AND AGAINST ANY AND ALL CLAIMS, LOSSES, LIABILITY, AND DAMAGES OF ANY KIND (INCLUDING REASONABLE ATTORNEYS’ FEES AND EXPENSES) ASSERTED AGAINST ANY OF THEM, INCURRED OR SUSTAINED IN CONNECTION WITH OR ARISING OUT OF ENTRANT’S PARTICIPATION IN THIS COMPETITION OR ANY TRAVEL OR OTHER ACTIVITY RELATED THERETO, USE OF ANY MODEL OR RED-TEAMING SYSTEM OR RIGHTS THEREIN, OR BREACH OF ANY AGREEMENT OR WARRANTY ASSOCIATED WITH THE COMPETITION, INCLUDING THESE OFFICIAL RULES. ANY ATTEMPT TO DELIBERATELY DAMAGE ANY WEBSITE OR UNDERMINE THE LEGITIMATE OPERATION OF THE COMPETITION MAY BE A VIOLATION OF CRIMINAL AND CIVIL LAWS AND, SHOULD SUCH AN ATTEMPT BE MADE, THE COMPETITION ENTITIES AND EACH OF THEIR LICENSEES RESERVE THE RIGHT TO SEEK ANY AND ALL REMEDIES AVAILABLE FROM ANY PERSONS RESPONSIBLE FOR ANY SUCH ATTEMPT TO THE FULLEST EXTENT PERMITTED BY LAW.

Each Entrant hereby acknowledges and agrees that the relationship between themselves and the Competition Entities is not a confidential, fiduciary, or other special relationship, and that the Entrant’s decision to provide the entry to Sponsor for purposes of the Competition does not place the Competition Entities in a position that is any different from the position held by members of the general public with regard to elements of the entry, other than as set forth in these Official Rules. Each Entrant understands and acknowledges that the Competition Entities have wide access to the models, technology, designs, and other materials, and that new ideas are constantly being submitted to them or being developed by their own employees. Each Entrant also acknowledges that many ideas may be competitive with, similar to, or identical to the model or red-teaming system submission in theme, idea, format, or other respects. Each Entrant acknowledges and agrees that such Entrant will not be entitled to any compensation as a result of Competition Entities' use of any such similar or identical material that has or may come to Competition Entities, or any of them, from other sources. Entrants acknowledge that other Entrants and Entrant Teams may have created ideas and concepts contained in their model or red-teaming system's design that may have familiarities or similarities to their system's design, and that they will not be entitled to any compensation or right to negotiate with the Competition Entities because of these familiarities or similarities.

Entrants further agree that the Competition Entities are not responsible for the following: (a) electronic transmissions, model or red-teaming system, entries, or notifications that are lost, late, stolen, incomplete, damaged, garbled, destroyed, misdirected, or not received by Sponsor or their agents for any reason; (b) any problems or technical malfunctions, errors, omissions, interruptions, deletions, defects, delays in operation or transmission, communication failures, and/or human error that may occur in the transmission, shipping errors or delays, receipt or processing of entries or related materials; or for destruction of or unauthorized access to, or alteration of, entries or related material; (c) failed or unavailable hardware, network, software, or telephone transmissions, damage to Entrants’ or any person’s computer and/or its contents related to or resulting from participation in this Competition; (d) causes that jeopardize the administration, security, fairness, integrity, or proper conduct of this Competition; (e) any entries submitted in a manner that is not expressly allowed under these Official Rules (all such entries will be disqualified); or (f) any printing errors in these Official Rules or in any advertisements or correspondence in connection with this Competition or the tabulation of Interaction Ratings or scores. Sponsor reserves the right, in its sole discretion, to cancel or suspend this Competition should virus, bugs, fraud, hacking, or other causes corrupt the administration, security, or proper play of the Competition, or in the event Sponsor does not receive a minimum of two qualified entries from separate eligible Entrant Teams. Sponsor further reserves the right, in its sole discretion, to cancel or suspend this Competition or to reschedule or reformat events, including without limitation the Summit or Finals Event, should Sponsor be prevented, in any manner whatsoever, from holding this Competition or any event due to any present or future law (whether or not valid); any act of God, earthquake, fire, flood, epidemic (including, without limitation, any pandemic), accident, explosion or casualty; any civil disturbance or armed conflict; or any other cause of any similar nature outside of Sponsor’s control. In all such cases, notice to this effect will be posted on the Competition Site and prizes to the extent awarded will be awarded as determined by Sponsor prior to cancellation. If, in Sponsor’s opinion, there is any suspected or actual evidence of electronic or non-electronic tampering with any portion of the Competition or if technical difficulties compromise the integrity of the Competition, the Sponsor reserves the right to void suspect entries and/or terminate the Competition and determine whether to award prizes in its sole discretion. Sponsor reserves the right, in its sole discretion, to disqualify any individual found by Sponsor to have tampered with the entry process or entry materials, otherwise interfered with the proper administration of the Competition, or violated these Official Rules.

DISPUTES: Except where prohibited, you agree that: (1) any and all disputes, claims, and causes of action arising out of or connected with this Competition or any prize awarded shall be resolved individually, without resort to any form of class action; (2) any and all claims, judgments, and awards shall be limited to actual out-of-pocket costs incurred, including costs associated with entering this Competition, but in no event attorneys’ fees; (3) the Competition Entities shall not be liable for, under no circumstances will you be permitted to obtain awards for, and you hereby waive all rights to claim, indirect, punitive, incidental, and consequential damages and any other damages (other than for actual out-of-pocket expenses), and any and all rights to have damages multiplied or otherwise increased. All issues and questions concerning the construction, validity, interpretation, and enforceability of these Official Rules, or the rights and obligations of the Entrant and Sponsor in connection with the Competition, shall be governed by, and construed in accordance with, the laws of the State of Washington without giving effect to any choice of law or conflict of law rules (whether of the State of Washington or any other jurisdiction), which would cause the application of the laws of any jurisdiction other than the State of Washington. You irrevocably submit to venue and exclusive personal jurisdiction in the federal and state courts in Seattle, King County, Washington, USA, for any dispute arising under these Official Rules or in connection with the Competition, and you waive all objections to jurisdiction and venue of such courts.

SPONSOR: Amazon.com Services LLC, 410 Terry Ave North, Seattle, Washington 98109, USA.

US, MD, Annapolis Junction
Are you excited to help the US Intelligence Community design, build, and implement AI algorithms to augment decision making while meeting the highest standards for reliability, transparency, and scalability? The Amazon Web Services (AWS) US Federal Professional Services team works directly with US Intelligence Community agencies and other public sector entities to achieve their mission goals through the adoption of Machine Learning (ML) methods. We build models for text, image, video, audio, and multi-modal use cases, using traditional or generative approaches to fit the mission. Our team collaborates across the entire AWS organization to bring access to product and service teams, to get the right solution delivered and drive feature innovation based on customer needs. At AWS, we're hiring experienced data scientists with a background in both traditional and generative AI who can help our customers understand the opportunities their data presents, and build solutions that earn the customer trust needed for deployment to production systems. In this role, you will work closely with customers to deeply understand their data challenges and requirements, and design tailored solutions that best fit their use cases. You should have broad experience building models using all kinds of data sources, and building data-intensive applications at scale. You should possess excellent business acumen and communication skills to collaborate effectively with stakeholders, develop key business questions, and translate requirements into actionable solutions. You will provide guidance and support to other engineers, sharing industry best practices and driving innovation in the field of data science and AI. This position may require local travel up to 25% It is expected to work from one of the above locations (or customer sites) at least 1+ days in a week. This is not a remote position. You are expected to be in the office or with customers as needed. This position requires that the candidate selected must currently possess and maintain an active TS/SCI Security Clearance with Polygraph. The position further requires the candidate to opt into a commensurate clearance for each government agency for which they perform AWS work. Key job responsibilities As an Data Scientist, you will: - Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate cutting-edge AI algorithms to address real-world challenges - Interact with customers directly to understand the business problem, help and aid them in implementation of AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production. - Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder - Provide customer and market feedback to Product and Engineering teams to help define product direction About the team About AWS Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
US, VA, Arlington
Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply cutting edge Generative AI algorithms to solve real world problems with significant impact? Amazon Web Services (AWS) Professional Services (ProServe) is looking for Data Scientists who like helping U.S. Federal agencies implement innovative cloud computing solutions and solve technical problems using state-of-the-art language models in the cloud. AWS ProServe engages in a wide variety of projects for customers and partners, providing collective experience from across the AWS customer base and are obsessed about strong success for the Customer. Our team collaborates across the entire AWS organization to bring access to product and service teams, to get the right solution delivered and drive feature innovation based upon customer needs. At AWS, we're hiring experienced data scientists with a background in NLP, generative AI, and document processing to help our customers understand, plan, and implement best practices around leveraging these technologies within their AWS cloud environments. Our consultants deliver proof-of-concept projects, reusable artifacts, reference architectures, and lead implementation projects to assist organizations in harnessing the power of their data and unlocking the potential of advanced NLP and AI capabilities. In this role, you will work closely with customers to deeply understand their data challenges and requirements, and design tailored solutions that best fit their use cases. You should have deep expertise in NLP/NLU, generative AI, and building data-intensive applications at scale. You should possess excellent business acumen and communication skills to collaborate effectively with stakeholders, develop key business questions, and translate requirements into actionable solutions. You will provide guidance and support to other engineers, sharing industry best practices and driving innovation in the field of data science and AI. It is expected to work from one of the above locations (or customer sites) at least 1+ days in a week. This is not a remote position. You are expected to be in the office or with customers as needed. This position requires that the candidate selected be a US Citizen and obtain and maintain a security clearance at the TS/SCI with polygraph level. Upon start, the selected candidate will be sponsored for a commensurate clearance for each government agency for which they perform AWS work. Key job responsibilities In this role, you will: - Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate cutting-edge generative AI solutions to address real-world challenges. - Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production. - Provide expertise and guidance in generative AI and document processing infrastructure, design, implementation, and optimization. - Maintain domain knowledge and expertise in generative AI, NLP, and NLU. - Architect and build large-scale solutions. - Build technical solutions that are secure, maintainable, scalable, reliable, performant, and cost-effective. - Identify and prepare metrics and reports for the internal team and for customers to delineate the value of their solution to the customer. - Identify, mitigate and communicate risks related to solution and service constraints by making technical trade-offs. - Participate in growing their team’s skills and help mentor internal and customer team members. - Provide guidance on the people, organizational, security and compliance aspects of AI/ML transformations for the customer. About the team Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
US, WA, Seattle
The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Applied Scientist with a strong deep learning background, to build industry-leading Generative Artificial Intelligence (GenAI) technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As a Applied Scientist with the AGI team, you will work with talented peers to lead the development of novel algorithms and modeling techniques, to advance the state of the art with LLMs. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in spoken language understanding. About the team The AGI team has a mission to push the envelope in GenAI with LLMs and multimodal systems, in order to provide the best-possible experience for our customers.
US, CA, Sunnyvale
Amazon's AGI Web & Knowledge Services group is seeking a passionate, talented, and inventive Applied Scientist to lead the development of industry-leading structured Information retrieval systems. As part of our cutting-edge AGI-SIR team, you will play a pivotal role in developing efficient AI solutions for Knowledge Graphs, Graph Search and Question Answering Systems. In this role, your work will focus on creating scalable and efficient AI-driven technologies that push the boundaries of information retrieval. You will work on a broad range of problems, from low-level data processing to the development of novel retrieval models, leveraging state-of-the-art machine learning methods. Key job responsibilities - Lead the development of advanced algorithms for knowledge graphs, graph search and question answering systems, guiding the team in solving complex problems and setting technical direction. - Design models that address customer needs, making informed trade-offs to balance accuracy, efficiency, and user experience. - Collaborate with engineering teams to implement successful models into scalable, reliable Amazon production systems. - Present results to technical and business audiences, ensuring clarity, statistical rigor, and relevance to business goals. - Establish and uphold high scientific and engineering standards, driving best practices across the team. - Promote a culture of experimentation and continuous learning within Amazon’s applied science community.
LU, Luxembourg
Are you interested in building state-of-the-art machine learning systems for the most complex, and fastest growing, transportation network in the world? If so, Amazon has the most exciting, and never-before-seen, challenges at this scale (including those in sustainability, e.g. how to reach net zero carbon by 2040). Amazon’s transportation systems get millions of packages to customers worldwide faster and cheaper while providing world class customer experience – from online checkout, to shipment planning, fulfillment, and delivery. Our software systems include services that use tens of thousands of signals every second to make business decisions impacting billions of dollars a year, that integrate with a network of small and large carriers worldwide, that manage business rules for millions of unique products, and that improve experience of over hundreds of millions of online shoppers. As part of this team you will focus on the development and research of machine learning solutions and algorithms for core planning systems, as well as for other applications within Amazon Transportation Services, and impact the future of the Amazon delivery network. Current research and areas of work within our team include machine learning forecast, uncertainty quantification, planning systems, model interpretability, graph neural nets, among others. We are looking for a Machine Learning Scientist with a strong academic background in the areas of machine learning, time series forecasting, and/or optimization. At Amazon, we strive to continue being the most customer-centric company on earth. To stay there and continue improving, we need exceptionally talented, bright, and driven people. If you'd like to help us build the place to find and buy anything online, and deliver in the most efficient and greenest way possible, this is your chance to make history. About the team The EU ATS Science and Technology (SnT) team owns scalable algorithms, models and systems that improve customer experience in middle-mile. We work backwards from Amazon's customers aiming to make transportation faster, cheaper, safer, more reliable and ecologically sustainable.
US, WA, Bellevue
We are a part of Amazon Alexa Devices organization with the mission “delight customers through contextual and personalized proactive experiences that keep customers informed, engaged, and productive without cognitive burden”. We are developing an advanced system using Large Language Model (LLM) technologies to deliver engaging, intuitive, and adaptive content recommendations across all Amazon surfaces. We aim to facilitate seamless reasoning and customer experiences, surpassing the capabilities of previous machine learning models. We are looking for a passionate, talented, and resourceful Applied Scientist in the field of Natural Language Processing (NLP), Recommender Systems and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware speech assistant. A successful candidate will have strong machine learning background and a desire to push the envelope in one or more of the above areas. The ideal candidate would also enjoy operating in dynamic environments, be self-motivated to take on challenging problems to deliver big customer impact, shipping solutions via rapid experimentation and then iterating on user feedback and interactions. Key job responsibilities As an Applied Scientist on the team, you will collaborate with other applied scientists and engineers to develop novel algorithms to enable timely, relevant and delightful recommendations and conversations. Your work will directly impact our customers in the form of products and services that make use of various machine learning, deep learning and language model technologies. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in the state of art.
IN, KA, Bengaluru
Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced ML systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real-world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning team for India Consumer Businesses. Machine Learning, Big Data and related quantitative sciences have been strategic to Amazon from the early years. Amazon has been a pioneer in areas such as recommendation engines, ecommerce fraud detection and large-scale optimization of fulfillment center operations. As Amazon has rapidly grown and diversified, the opportunity for applying machine learning has exploded. We have a very broad collection of practical problems where machine learning systems can dramatically improve the customer experience, reduce cost, and drive speed and automation. These include product bundle recommendations for millions of products, safeguarding financial transactions across by building the risk models, improving catalog quality via extracting product attribute values from structured/unstructured data for millions of products, enhancing address quality by powering customer suggestions We are developing state-of-the-art machine learning solutions to accelerate the Amazon India growth story. Amazon India is an exciting place to be at for a machine learning practitioner. We have the eagerness of a fresh startup to absorb machine learning solutions, and the scale of a mature firm to help support their development at the same time. As part of the India Machine Learning team, you will get to work alongside brilliant minds motivated to solve real-world machine learning problems that make a difference to millions of our customers. We encourage thought leadership and blue ocean thinking in ML. Key job responsibilities Use machine learning and analytical techniques to create scalable solutions for business problems Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes Design, develop, evaluate and deploy, innovative and highly scalable ML models Work closely with software engineering teams to drive real-time model implementations Work closely with business partners to identify problems and propose machine learning solutions Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model maintenance Work proactively with engineering teams and product managers to evangelize new algorithms and drive the implementation of large-scale complex ML models in production Leading projects and mentoring other scientists, engineers in the use of ML techniques About the team International Machine Learning Team is responsible for building novel ML solutions that attack India first (and other Emerging Markets across MENA and LatAm) problems and impact the bottom-line and top-line of India business. Learn more about our team from https://www.amazon.science/working-at-amazon/how-rajeev-rastogis-machine-learning-team-in-india-develops-innovations-for-customers-worldwide
US, WA, Seattle
Come be a part of a rapidly expanding $35 billion-dollar global business. At Amazon Business, we set out every day to innovate and disrupt the status quo. We stand at the intersection of tech and retail in the B2B space developing innovative purchasing and procurement solutions to help businesses and organizations re-imagine buying. Bring your insight, imagination and a healthy disregard for the impossible. Join us in building and celebrating the value of Amazon Business to buyers and sellers of all sizes, unlocking our potential worldwide. Amazon Business Supplier Experience Science team is looking for Sr. Applied Scientist to excel at product and service pricing, selection, forecast and optimization. Amazon Business (AB) represents an incredible opportunity to address a vast new market segment and customer base for Amazon. We are focused on building solutions that enable B2B customers to find, research, and buy products and services across multiple devices and marketplaces. The Amazon Business Science team owns the science and analytics for key AB problems including price setting, selection additions and operations optimization. Amazon Business is a fast growing business sector. We need leaders who can think big and drive big vision into a reality. Please come to work with us if you are result driven, think big, and want to have fun and make a history. You will build the science models and the supporting structures needed to analyze, dive deep, and innovate the pricing strategies. You will also have the opportunity to present findings to cross functional team partners to drive improvements. You will work closely with other Applied/Research/Data Scientists, Economists, Data Engineers, Software Development Engineers, Program Managers and Business Partners to solve challenging problems. You need be comfortable using intellect, curiosity and technical ability to develop innovative solutions to business problems. You need learn different aspects of the business and understand how to apply science and analytics to solve high impact business problems. You will be expected to provide clear and concise explanation to results and approaches as well as provide opinion and guidance on problem solving. The ideal candidate will have leadership skills, proven ability to develop, enhance, automate, and manage science models from end to end. The ideal candidate will have data mining and modeling skills and will be comfortable facilitating idea creation and working from concept through to execution. The ideal candidate must have the ability to manage medium-scale automation and modeling projects, identify requirements and build methodology and tools that are mathematically grounded but also explainable operationally, apply technical skills allowing the models to adapt to changing attributes. Key job responsibilities • Contribute to supplier operations strategy development based on science models and data analysis • Develop models to measure long term impact of seller behaviors • Collaborate with product and engineering teams both within and outside of AB to launch selection and operations systems based on science and data. • Use optimization, statistical, machine learning and analytical techniques to create scalable solutions for business problems. • Design, development and evaluation of highly innovative models for forecast, optimization and experimentation. • Work and collaborate effectively with product managers and software engineering teams to build algorithms and models and integrate successful models and algorithms in production systems. • Contribute to Amazon's Intellectual Property through patents and internal and external publications A day in the life The scientist will develop, enhance, automate, and manage science models from end to end. The scientist will also have the opportunity to present findings to cross functional team partners to drive improvements. The scientist will work with other Applied/Research/Data Scientists, Economists, Data Engineers, Software Development Engineers, Program Managers and Business Partners to build analytical and science models. The scientist will be expected to provide clear and concise explanation to results and approaches as well as provide opinion and guidance on problem solving. About the team Amazon Business (AB) represents an incredible opportunity to address a vast new market segment and customer base for Amazon. We are focused on building solutions that enable B2B customers to find, research, and buy products and services across multiple devices and marketplaces. The Amazon Business Science team owns the science and analytics for key AB problems including price setting and selection additions.
US, WA, Bellevue
The Artificial General Intelligence (AGI) team is looking for a highly skilled and experienced Senior Research Scientist, to lead the development of cutting-edge algorithms and models for supervised fine-tuning and reinforcement learning through human feedback; with a focus across text, image, and video modalities. As a Senior Research Scientist, you will play a critical role in driving the development of Generative AI (GenAI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. Key job responsibilities - Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in GenAI - Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results - Think big about the arc of development of GenAI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems - Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports - Mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the team
US, WA, Seattle
The Private Brands Discovery team designs innovative machine learning solutions to drive customer awareness for Amazon’s own brands and help customers discover products they love. Private Brands Discovery is an interdisciplinary team of Scientists and Engineers, who incubate and build disruptive solutions using cutting-edge technology to solve some of the toughest science problems at Amazon. To this end, the team employs methods from Natural Language Processing, Deep learning, multi-armed bandits and reinforcement learning, Bayesian Optimization, causal and statistical inference, and econometrics to drive discovery across the customer journey. Our solutions are crucial for the success of Amazon’s own brands and serve as a beacon for discovery solutions across Amazon. This is a high visibility opportunity for someone who wants to have business impact, dive deep into large-scale problems, enable measurable actions on the consumer economy, and work closely with scientists and engineers. As a scientist, you bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions.. With a focus on bias for action, this individual will be able to work equally well with Science, Engineering, Economics and business teams. Key job responsibilities - Drive applied science projects in machine learning end-to-end: from ideation over prototyping to launch. For example, starting from deep scientific thinking about new ways to support customers’ journeys through discovery, you analyze how customers discover, review and purchase Private Brands to innovate marketing and merchandising strategies. - Propose viable ideas to advance models and algorithms, with supporting argument, experiment, and eventually preliminary results. - Invent ways to overcome technical limitations and enable new forms of analyses to drive key technical and business decisions. - Present results, reports, and data insights to both technical and business leadership. - Constructively critique peer research and mentor junior scientists and engineers. - Innovate and contribute to Amazon’s science community and external research communities.