Luciana Buriol is seen standing in front of a large whiteboard filled with equations, she is standing toward the center, smiling with her hands clasped behind her back
Luciana Buriol is a principal research scientist within Amazon's Supply Chain Optimization Technologies (SCOT) organization, where she focuses on optimizing Amazon’s distribution network.
Courtesy of Luciana Buriol

Luciana Buriol’s quest for scientific joy

The principal research scientist shares lessons learned during her life journey from a small farm to working on optimizing Amazon’s distribution network.

[Editor's note: Luciana Buriol was recently named an International Federation of Operational Research Societies (IFORS) Distinguished Lecturer, a program established in 1999 to recognize distinguished operations research scholars. In that capacity, she delivered a keynote at INFORMS 2022 titled,"The Amazon Fulfillment Network: Topology and Capacity Planning".]

For more than two decades Luciana Buriol has had a hand in building systems that impact our lives. From how ambulances are positioned across a city to save the most lives or how millions of orders arrive at the right door on time. And even after 20 years as a leader in her profession, she exudes a level of delight and curiosity that leaves a lasting impression.

One of six siblings who grew up on a small farm in Brazil, outside a remote farming village, computer science was never on Buriol’s radar. But in the late 1980s a middle school teacher noticed her aptitude for numbers and encouraged her to participate in a BASIC programming course.

Luciana Buriol is seen in a selfie with her daughter and husband
Luciana Buriol, seen here with her daughter and husband who moved with her to the US from Brazil, says she finds a way each day to pursue what she calls her “scientific joy”.
Luciana Buriol

Mentors, professors, and teachers like that spanned her entire education. After middle school, a high school physics teacher pointed her toward computer science. An undergraduate professor introduced her to optimization and convinced her to move to Sao Paulo. They all had a clear vision of the possibilities and Buriol’s potential. “They were my angels,” she says, pointing her toward opportunities she might never have known about otherwise.

“Professors are so important in the life of kids, especially the kids whose parents and environment can’t point them toward opportunities,” Buriol adds.

One of her PhD advisors, Mauricio Resende, recalls their first meeting outside a countryside hotel in 1999 the night before a conference. Buriol walked up with luggage in tow. She was just off a six-hour interstate bus ride, a two-hour intercity bus ride, and a long walk in the dark from the bus station. “That was one thing that impressed me, her determination to be there,” said Resende, who advised Buriol’s research at AT&T and now is her colleague and a principal research scientist at Amazon.

A year after their meeting, Resende, then senior principal scientist at AT&T Research, became one of Buriol’s advisors after helping her switch her PhD project. At the time she was attending Universidade Estadual de Campinas, pursuing her PhD degree in electrical engineering. She had been optimizing ambulance garage locations in São Paulo — a city of 17 million people at the time — based on emergency call data. But then she learned from Resende that AT&T had a different yet similar problem.

Related content
Danielle Maddix Robinson's mathematics background helps inform robust models that can predict everything from retail demand to epidemiology.

“At the time AT&T needed to grow a lot and quickly,” Buriol said. “The traffic of telecom networks was rapidly increasing.” So in 2001 she moved to New Jersey. She was specifically tasked with algorithms for network design and operation, deciding which nodes should be connected, and with what capacity, to optimize resource utilization for AT&T’s USA telecommunication network. Resende said her work was a resounding success — in fact it became essential to so many groups that AT&T invited her to stay an additional four months.

“Immediately she was very successful not only in the work with me but in her many collaborations with other people at AT&T. She was one of the most successful PhD students who went through AT&T,” Resende said.

She brought the same determination Resende had witnessed at the conference years before to her code. She was constantly optimizing algorithms. At the time, she said, she assumed everyone wrote that way. Implementing efficiently, planning ahead, choosing data structures for the most efficient code, that was normal to her. But when she worked at AT&T during her PhD, her technique quickly impressed her new colleagues. “They’d say things like, ’How did you do that?’” She quickly became an asset to multiple groups.

Luciana Buriol discusses her career

In 2002 she moved back to Brazil to finish her dissertation. And in 2005, after an 18-month postdoc in the Computer Science Department at Sapienza University, she moved back to Brazil for an associate professorship in computer science.

The position was at Federal University of Rio Grande do Sul (UFRGS), where she spent 15 years teaching and challenging her students to solve some of their university and city’s largest challenges. However, she noted, she found herself curious about other challenges.

“At some point, even the best code has an upper limit,” Buriol said. “At a certain scale the system has to be replanned.” Buriol had always been curious about these limitations and how companies solved problems too big for algorithms. For 15 years she taught and funneled students into some of the most prestigious computer science positions in the world. She led national and international scientific organizations. But all the while she wondered how the world’s biggest data problems were being solved.

Related content
Amazon's Daliana Liu helps others in the field chart their own paths.

Meanwhile, Resende had joined Amazon in December 2014 as a principal research scientist. The two had remained in consistent communication since Buriol’s time in New Jersey. Her students became his students and interns. They collaborated on projects.

So when Buriol started asking about exposure to Amazon — a company that was solving the problems of scale that were on her mind — it was a no brainer for Resende. He suggested she apply for the Amazon Scholar program. She was accepted for a 3-month project in 2019 and said she never planned to stay, just to learn.

“Those three months made her change her mind,” Resende said. “She was very interested in exploring opportunities for a full-time position.”

In 2021 she accepted a full-time position with the Supply Chain Optimization Technologies (SCOT) organization. Her work with the SCOT team resembles the PhD research from 20 years ago. Instead of optimizing nodes and links of a telecommunication network, she’s optimizing Amazon’s distribution network.

“I love this project. When I thought about coming to Amazon, this is what I wanted to do. It’s a huge problem, complex, and it demands that we be talking with people from different groups,” she said.

Related content
Belinda Zeng, head of applied science and engineering at Amazon Search Science and AI, shares her perspective.

As a former professor, Buriol is in a unique position to advise young scientists. First and foremost, she says to be happy Buriol said she finds a way each day to pursue what she calls her “scientific joy”.

Her second piece of advice: Collaborate. “Sometimes people are very good from a technical skills perspective, but not good at collaboration,” she says. “If you share what you’re doing and ask questions, your projects will be better from the very beginning. Always be on the lookout for opportunities to help others, ask for help, and share your work.”

Finally, Buriol says, don’t settle. “You can always learn something new or do something even better than what you were.”

informs_logo.png
INFORMS 2022
The world's largest operations research and analytics conference is taking place in Indianapolis, Indiana. The SCOT team's methodologies and mechanisms will be a topic of conversation at the conference.

Related content

US, CA, Santa Clara
Amazon is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help build industry-leading language technology. Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Processing (NLP), Generative AI, Large Language Model (LLM), Natural Language Understanding (NLU), Machine Learning (ML), Retrieval-Augmented Generation, Responsible AI, Agent, Evaluation, and Model Adaptation. As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services, as well as contributing to the wider research community. You will gain hands on experience with Amazon’s heterogeneous text and structured data sources, and large-scale computing resources to accelerate advances in language understanding. The Science team at AWS Bedrock builds science foundations of Bedrock, which is a fully managed service that makes high-performing foundation models available for use through a unified API. We are adamant about continuously learning state-of-the-art NLP/ML/LLM technology and exploring creative ways to delight our customers. In our daily job we are exposed to large scale NLP needs and we apply rigorous research methods to respond to them with efficient and scalable innovative solutions. At AWS Bedrock, you’ll experience the benefits of working in a dynamic, entrepreneurial environment, while leveraging AWS resources, one of the world’s leading cloud companies and you’ll be able to publish your work in top tier conferences and journals. We are building a brand new team to help develop a new NLP service for AWS. You will have the opportunity to conduct novel research and influence the science roadmap and direction of the team. Come join this greenfield opportunity! About the team AWS Bedrock Science Team is a part of AWS Utility Computing AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. About the team 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 we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
GB, MLN, Edinburgh
We’re looking for a Machine Learning Scientist in the Personalization team for our Edinburgh office experienced in generative AI and large models. You will be responsible for developing and disseminating customer-facing personalized recommendation models. This is a hands-on role with global impact working with a team of world-class engineers and scientists across the Edinburgh offices and wider organization. You will lead the design of machine learning models that scale to very large quantities of data, and serve high-scale low-latency recommendations to all customers worldwide. You will embody scientific rigor, designing and executing experiments to demonstrate the technical efficacy and business value of your methods. You will work alongside a science team to delight customers by aiding in recommendations relevancy, and raise the profile of Amazon as a global leader in machine learning and personalization. Successful candidates will have strong technical ability, focus on customers by applying a customer-first approach, excellent teamwork and communication skills, and a motivation to achieve results in a fast-paced environment. Our position offers exceptional opportunities for every candidate to grow their technical and non-technical skills. If you are selected, you have the opportunity to make a difference to our business by designing and building state of the art machine learning systems on big data, leveraging Amazon’s vast computing resources (AWS), working on exciting and challenging projects, and delivering meaningful results to customers world-wide. Key job responsibilities Develop machine learning algorithms for high-scale recommendations problems. Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative analysis and business judgement. Collaborate with software engineers to integrate successful experimental results into large-scale, highly complex Amazon production systems capable of handling 100,000s of transactions per second at low latency. Report results in a manner which is both statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment.
US, MA, Westborough
Amazon is looking for talented Postdoctoral Scientists to join our Fulfillment Technology and Robotics team for a one-year, full-time research position. The Innovation Lab in BOS27 is a physical space in which new ideas can be explored, hands-on. The Lab provides easier access to tools and equipment our inventors need while also incubating critical technologies necessary for future robotic products. The Lab is intended to not only develop new technologies that can be used in future Fulfillment, Technology, and Robotics products but additionally promote deeper technical collaboration with universities from around the world. The Lab’s research efforts are focused on highly autonomous systems inclusive of robotic manipulation of packages and ASINs, multi-robot systems utilizing vertical space, Amazon integrated gantries, advancements in perception, and collaborative robotics. These five areas of research represent an impactful set of technical capabilities that when realized at a world class level will unlock our desire for a highly automated and adaptable fulfillment supply chain. As a Postdoctoral Scientist you will be developing a coordinated multi-agent system to achieve optimized trajectories under realistic constraints. The project will explore the utility of state-of-the-art methods to solve multi-agent, multi-objective optimization problems with stochastic time and location constraints. The project is motivated by a new technology being developed in the Innovation Lab to introduce efficiencies in the last-mile delivery systems. Key job responsibilities In this role you will: * Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s diverse global science community. * Publish your innovation in top-tier academic venues and hone your presentation skills. * Be inspired by challenges and opportunities to invent new techniques in your area(s) of expertise.
US, WA, Seattle
Here at Amazon, we embrace our differences. We are committed to furthering our culture of diversity and inclusion of our teams within the organization. We’re working on the future. If you are seeking an iterative fast-paced environment where you can drive innovation, apply state-of-the-art technologies to solve extreme-scale real world delivery challenges, and provide visible benefit to end-users, this is your opportunity. Come work on the Amazon Prime Air team We're looking for outstanding scientists and engineers who combine superb technical, research and analytical capabilities with a demonstrated ability architect complex hardware, software, embedded, mobile and mission-critical systems to ensure they can be found compliant to DO-178C. This person must be comfortable working with a team of top-notch software, hardware and applied science Engineers. We’re looking for people who innovate and love solving hard problems. You will work hard, have fun, and of course, make history! Export License Control This position may require a deemed export control license for compliance with applicable laws and regulations. Placement is contingent on Amazon’s ability to apply for and obtain an export control license on your behalf. Key job responsibilities The manager of the High Fidelity Modeling group will lead a group of engineers and scientists that provide computational fluid dynamics modeling, as well as aerodynamic and other surrogate models used in flight simulation of the Prime Air drones.
US, WA, Seattle
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! In Prime Video READI, our mission is to automate infrastructure scaling and operational readiness. We are growing a team specialized in time series modeling, forecasting, and release safety. This team will invent and develop algorithms for forecasting multi-dimensional related time series. The team will develop forecasts on key business dimensions with optimization recommendations related to performance and efficiency opportunities across our global software environment. As a founding member of the core team, you will apply your deep coding, modeling and statistical knowledge to concrete problems that have broad cross-organizational, global, and technology impact. Your work will focus on retrieving, cleansing and preparing large scale datasets, training and evaluating models and deploying them to production where we continuously monitor and evaluate. You will work on large engineering efforts that solve significantly complex problems facing global customers. You will be trusted to operate with complete independence and are often assigned to focus on areas where the business and/or architectural strategy has not yet been defined. You must be equally comfortable digging in to business requirements as you are drilling into design with development teams and developing production ready learning models. You consistently bring strong, data-driven business and technical judgment to decisions. You will work with internal and external stakeholders, cross-functional partners, and end-users around the world at all levels. Our team makes a big impact because nothing is more important to us than delivering for our customers, continually earning their trust, and thinking long term. You are empowered to bring new technologies to your solutions. If you crave a sense of ownership, this is the place to be.
US, WA, Seattle
Amazon Advertising operates at the intersection of eCommerce and advertising, and is investing heavily in building a world-class advertising business. We are defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products to improve both shopper and advertiser experience. With a broad mandate to experiment and innovate, we grow at an unprecedented rate with a seemingly endless range of new opportunities. The Ad Response Prediction team in Sponsored Products organization build advanced deep-learning models, large-scale machine-learning pipelines, and real-time serving infra to match shoppers’ intent to relevant ads on all devices, for all contexts and in all marketplaces. Through precise estimation of shoppers’ interaction with ads and their long-term value, we aim to drive optimal ads allocation and pricing, and help to deliver a relevant, engaging and delightful ads experience to Amazon shoppers. As the business and the complexity of various new initiatives we take continues to grow, we are looking for talented Applied Scientists to join the team. Key job responsibilities As a Applied Scientist II, you will: * Conduct hands-on data analysis, build large-scale machine-learning models and pipelines * Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production * Run regular A/B experiments, gather data, perform statistical analysis, and communicate the impact to senior management * Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving * Provide technical leadership, research new machine learning approaches to drive continued scientific innovation * Be a member of the Amazon-wide Machine Learning Community, participating in internal and external MeetUps, Hackathons and Conferences
IN, HR, Gurugram
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, VA, Arlington
Are you passionate about programming languages, applying formal verification, program analysis, constraint-solving, and/or theorem proving to real world problems? Do you want to create products that help customers? If so, then we have an exciting opportunity for you. In this role, you will interact with internal teams and external customers to understand their requirements. You will apply your knowledge to propose innovative solutions, create software prototypes, and productize prototypes into production systems using software development tools and methodologies. In addition, you will support and scale your solutions to meet the ever growing demand of customer use. Technical Responsibilities: - Interact with various teams to develop an understanding of their security and safety requirements. - Apply the acquired knowledge to build tools find problems, or show the absence of security/safety problems. - Implement these tools through the use of SAT, SMT, and various concepts from programming languages, theorem proving, formal verification and constraint solving. - Perform analysis of the customer systems using tools developed in-house or externally provided - Create software prototypes to verify and validate the devised solutions methodologies; integrate the prototypes into production systems using standard software development tools and methodologies. Leadership Responsibilities: - Can present and defend company-wide technical decisions to the internal technical community and represent the company effectively at technical conferences. - Functional thought leader, sought after for key tech decisions. Can successfully sell ideas to an executive level decision maker. - Mentors and trains the research scientist community on complex technical issues. AWS has the most services and more features within those services, than any other cloud provider–from infrastructure technologies like compute, storage, and databases–to emerging technologies, such as machine learning and artificial intelligence, data lakes and analytics, and Internet of Things. Whether its Identity features such as access management and sign on, cryptography, console, builder & developer tools, and even projects like automating all of our contractual billing systems, AWS Platform is always innovating with the customer in mind. The AWS Platform team sustains over 750 million transactions per second. We have a formal mentor search application that lets you find a mentor that works best for you based on location, job family, job level etc. Your manager can also help you find a mentor or two, because two is better than one. In addition to formal mentors, we work and train together so that we are always learning from one another, and we celebrate and support the career progression of our team members. Key job responsibilities Technical Responsibilities: - Interact with various teams to develop an understanding of their security and safety requirements. - Apply the acquired knowledge to build tools find problems, or show the absence of security/safety problems. - Implement these tools through the use of SAT, SMT, BDDs, and various concepts from programming languages, theorem proving, formal verification and constraint solving. - Perform analysis of the customer systems using tools developed in-house or externally provided - Create software prototypes to verify and validate the devised solutions methodologies; integrate the prototypes into production systems using standard software development tools and methodologies. Leadership Responsibilities: - Can present and defend company-wide technical decisions to the internal technical community and represent the company effectively at technical conferences. - Functional thought leader, sought after for key tech decisions. Can successfully sell ideas to an executive level decision maker. - Mentors and trains the research scientist community on complex technical issues. A day in the life You will be working on cutting edge technology related to formal methods, automated reasoning, automated testing, and adjacent areas. You will work with fellow applied scientists to solve challenging problems that provide value to customers by improving the quality of software. You will have an opportunity to publish your work. 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. AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. 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 we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Mentorship and 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. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred 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. About the team The Automated Reasoning in Identity (ARI) team is growing fast. It works on applying automated reasoning techniques to services within AWS's Identity organization, building on initial successes of the Zelkova and Access Analyzer projects. The reach of AR within Identity is growing, with more scientists joining all the time.
US, CA, Sunnyvale
The Artificial General Intelligence (AGI) team is looking for a highly skilled and experienced Senior Applied Scientist, to lead the development and implementation 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 Applied 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, CA, Sunnyvale
The Artificial General Intelligence (AGI) team is looking for a highly skilled and experienced Senior Applied Scientist, to lead the development and implementation 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 Applied 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