Careers

The Amazon Fulfillment Technologies (AFT) Science team is looking for an exceptional Applied Scientist, with strong optimization and analytical skills, to develop production solutions for one of the most complex systems in the world: Amazon’s Fulfillment Network. At AFT Science, we design, build and deploy optimization, simulation, and machine learning solutions to power the production systems running at world wide Amazon Fulfillment Centers. We solve a wide range of problems that are encountered in the network, including labor planning and staffing, demand prioritization, pick assignment and scheduling, and flow process optimization. We are tasked to develop innovative, scalable, and reliable science-driven solutions that are beyond the published state of art in order to run frequently (ranging from every few minutes to every few hours per use case) and continuously in our large scale network. Key job responsibilities As an Applied Scientist, you will work with other scientists, software engineers, product managers, and operations leaders to develop scientific solutions and analytics using a variety of tools and observe direct impact to process efficiency and associate experience in the fulfillment network. Key responsibilities include: * Develop an understanding and domain knowledge of operational processes, system architecture and functions, and business requirements * Deep dive into data and code to identify opportunities for continuous improvement and/or disruptive new approach * Develop scalable mathematical models for production systems to derive optimal or near-optimal solutions for existing and new challenges * Create prototypes and simulations for agile experimentation of devised solutions * Advocate technical solutions to business stakeholders, engineering teams, and senior leadership * Partner with engineers to integrate prototypes into production systems * Design experiment to test new or incremental solutions launched in production and build metrics to track performance A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! About the team Amazon Fulfillment Technology (AFT) designs, develops and operates the end-to-end fulfillment technology solutions for all Amazon Fulfillment Centers (FC). We harmonize the physical and virtual world so Amazon customers can get what they want, when they want it. The AFT Science team has expertise in operations research, optimization, scheduling, planning, simulation, and machine learning. We also have domain expertise in the operational processes within the FCs and their defects. We prioritize advancements that support AFT tech teams and focus areas rather than specific fields of research or individual business partners. We influence each stage of innovation from inception to deployment which includes both developing novel solutions or improving existing approaches. Resulting production systems rely on a diverse set of technologies, our teams therefore invest in multiple specialties as the needs of each focus area evolves.

On every page at Amazon, we need to decide what content would be most helpful to customers - ranging from automated recommendations to manual merchandising to navigational or informational content, etc. What do we show to customers to help them make shopping decisions and help them discover more parts of Amazon's vast catalog? In Personalization, we rely heavily on A/B testing to answer this question by running experiments on some of Amazon’s most prominent and valuable pages. About our team: We are the Core Recommendations team under Personalization. We are heavily data-driven, and focus on analyzing existing customer metrics around customer engagement and identifying possible improvements. We then prototype novel features and new models and collect data by running controlled experiments. We quickly reject ideas that fail and double down on those that show promise. Our most successful projects are born from the ground up and our scientists and engineers are encouraged to pitch ideas and lead them to completion. About the role: Our team works across the stack to come up with stable, responsive, secure, accessible & cross-platform customer experiences. Project opportunities as an applied scientist range from backend big data builds, LLMs, and developing other ML models, pipelines, and features. Successful candidates must also be innovative, flexible, self-directed, and able to design and write high-performance, reliable, maintainable code. This role requires the ability to creatively deal with ambiguity, be data-driven and juggle cross-organization complexity. If you enjoy working in a dynamic environment to deliver world class mission critical systems, this may be the career opportunity for you!

We’re working to improve shopping on Amazon using the conversational capabilities of large language models, and are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. You'll be working with talented scientists, engineers, and technical program managers (TPM) to innovate on behalf of our customers. If you're fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey! Key job responsibilities We seek strong Applied Scientists with domain expertise in machine learning and deep learning, transformers, generative models, large language models, computer vision and multimodal models. You will devise innovative solutions at scale, pushing the technological and science boundaries. You will guide the design, modeling, and architectural choices of state-of-the-art large language models and multimodal models. You will devise and implement new algorithms and new learning strategies and paradigms. You will be technically hands-on and drive the execution from ideation to productionization. You will work in collaborative environment with other technical and business leaders, to innovate on behalf of the customer.

Help re-invent how millions of people watch TV! Fire TV remains the #1 best-selling streaming media player in the US. Our goal is to be the global leader in delivering entertainment inside and outside the home, with the broadest selection of content, devices and experiences for customers. Our science team works at the intersection of Recommender Systems, Information Retrieval, Machine Learning and Natural Language Understanding. We leverage techniques from all these fields to create novel algorithms that allow our customers to engage with the right content at the right time. Our work directly contributes to making our devices delightful to use and indispensable for the household. Key job responsibilities - Drive new initiatives applying Machine Learning techniques to improve our recommendation, search and entity matching algorithms - Perform hands-on data analysis and modeling with large data sets to develop insights that increase device usage and customer experience - Design and run A/B experiments, evaluate the impact of your optimizations and communicate your results to various business stakeholders - Work closely with product managers and software engineers to design experiments and implement end-to-end solutions - Setup and monitor alarms to detect anomalous data patterns and perform root cause analyses to explain and address them - Be a member of the Amazon-wide Machine Learning Community, participating in internal and external MeetUps, Hackathons and Conferences - Help attract and recruit technical talent; mentor junior scientists

Help re-invent how millions of people watch TV! Fire TV remains the #1 best-selling streaming media player in the US. Our goal is to be the global leader in delivering entertainment inside and outside the home, with the broadest selection of content, devices and experiences for customers. Our science team works at the intersection of Recommender Systems, Information Retrieval, Machine Learning and Natural Language Understanding. We leverage techniques from all these fields to create novel algorithms that allow our customers to engage with the right content at the right time. Our work directly contributes to making our devices delightful to use and indispensable for the household. Key job responsibilities - Drive new initiatives applying Machine Learning techniques to improve our recommendation, search and entity matching algorithms - Perform hands-on data analysis and modeling with large data sets to develop insights that increase device usage and customer experience - Design and run A/B experiments, evaluate the impact of your optimizations and communicate your results to various business stakeholders - Work closely with product managers and software engineers to design experiments and implement end-to-end solutions - Setup and monitor alarms to detect anomalous data patterns and perform root cause analyses to explain and address them - Be a member of the Amazon-wide Machine Learning Community, participating in internal and external MeetUps, Hackathons and Conferences - Help attract and recruit technical talent; mentor junior scientists

Appstore Quality tech team builds tools, using AI and engineering techniques to provide the best quality apps to Amazon Appstore users. We are a team of highly-motivated, engaged, and responsive professionals who enable the core testing and quality infrastructure of Amazon Appstore. Come join our team and be a part of history as we deliver results for our customers. Appstore Quality team's mission is to automate all types of functional, non functional, and compliance checks on apps submitted by appstore app developers to enable north star vision of publishing apps in under 5 hours. Our team uses various ML/AI/Generative AI techniques to automatically detect violations in images and text metadata submitted by developers. We are working on ambitious project AI projects such as building LLM, auto navigate a mobile app to detect inside app issues and violations. We are seeking an innovative and technically strong data scientist with a background in optimization, machine learning, and statistical modeling/analysis. This role requires a team member to have strong quantitative modeling skills and the ability to apply optimization/statistical/machine learning methods to complex decision-making problems, with data coming from various data sources. The candidate should have strong communication skills, be able to work closely with stakeholders and translate data-driven findings into actionable insights. The successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and ability to work in a fast-paced and ever-changing environment. This role involves working closely with Sr Data Scientist, Principal engineer, and engineering team to build ML and AL based solutions in meeting our north start vision. Key job responsibilities • Implement statistical methods to solve specific business problems utilizing code (Python, Scala, etc.). • Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters. • Collaborate with program management, product management, software developers, data engineering, and business leaders to provide science support, and communicate feedback; develop, test and deploy a wide range of statistical, econometric, and machine learning models. • Build customer-facing reporting tools to provide insights and metrics which track model performance and explain variance. • Communicate verbally and in writing to business customers with various levels of technical knowledge, educating them about our solutions, as well as sharing insights and recommendations. • Earn the trust of your customers by continuing to constantly obsess over their needs and helping them solve their problems by leveraging technology • Excellent prompt engineering skillset with a deep knowledge of LLMs, embeddings, transformer models. • Work with distributed machine learning and statistical algorithms to harness enormous volumes of data at scale to serve our customers About the team In Appstore, “We entertain, and delight, hundreds of millions of people across devices with a vast selection of relevant apps, games, and services by making it trivially easy for developers to deliver”. Appstore team enables the customer and developer flywheel on devices by enabling developers to seamlessly launch and manage their apps/ in-app content on Amazon. It helps customers discover, buy and engage with these apps on Fire TV, Fire Tablets and mobile devices. The technologies we build on vary from device software, to high scale services, to efficient tools for developers.

Amazon is looking for talented Postdoctoral Scientists to join our Amazon Robotics team for a one-year, full-time research position. Postdoctoral Scientists will innovate in key areas of machine learning, reinforcement learning, and foundational models for robotic manipulation. The Postdoc will research, propose, and develop a generalizable robotic pick and pack policy by leveraging the state-of-the-art diffusion polices, data-efficient reinforcement learning methods, and foundation models for robotic perception and manipulation. The Postdoc will evaluate the performance of such a policy on at least two hardware platforms, and iteratively improve the performance on a variety of hardware configurations. Key job responsibilities • Research vision - Where should we be focusing our efforts in this rapidly developing field • Research delivery – Proving/dis-proving strategies and methodologies, innovating and iterating ML solutions for robotic manipulation • Research results - Publish your innovation in top-tier academic venues and hone your presentation skills. A day in the life • Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise. • Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community. About the team The Manipulation Research Team aims to answer ambiguous open questions in the domain of robotic manipulation. We focus on generalizable machine learning models and multi-modalities in robotic grasping in order to impact a broad range of robotic manipulation applications across Amazon Fulfillment Network (AFN).

Amazon CloudWatch is the native AWS monitoring and observability service for cloud resources and applications. We are seeking a talented Senior Applied Scientist to develop next-generation scientific methods and infrastructure to support a core AWS business that delivers critical services to millions of customers operating at scale. This is a high visibility and high impact role that work on highly strategic projects in the AI/ML and Analytics space, will interact with all levels of AWS leadership. We are developing solutions that not only surface the “what” but also the “why” and “how to fix it”, without requiring operators to have extensive domain knowledge and technical expertise to efficiently troubleshoot and remediate incidents. Using decades of AWS operational excellence coupled with the advances in LLMs and Gen-AI technologies, we are transforming the very core of how customers can effortlessly interact with our offerings to build and operate their applications in the cloud. We are hiring to grow our team, and are looking for well-rounded applied scientists with backgrounds in machine learning, foundation models, and natural language processing. You'll be working with talented scientists, engineers, and product managers to innovate on behalf of our customers. If you're fired up about being part of a dynamic, mission driven team, then this is your moment to join us on this exciting journey! Key job responsibilities As a Sr. Applied Scientist you will be responsible for * Research and development of algorithms that improve training of foundation models across pre-training, multitask learning, supervised finetuning, and reinforcement learning from human feedback * Research and development of novel approaches for anomaly detection, root cause analysis, and provide intelligent insights from vast amounts of monitoring and observability data * Collaborating with scientists, engineers, and Product Managers across CloudWatch team as well as directly with customers * Lead key science initiatives in strategic investment areas of AI/ML/LLM Ops and Observability * Be an industry thought leader representing Amazon at top-tier scientific conferences * Engaging in the hiring process and developing, growing, and mentoring junior scientists A day in the life Working closely with and across agile teams, you will be able to see and feel the impact of your work on our customers. This is a high visibility and high impact role that will interact with all levels of AWS leadership. Our ideal candidate is excited about the incredible opportunity that cloud monitoring represents and is deeply passionate about delivering the highest quality services leveraging AI/ML/LLMs. You’re naturally customer centric and thrive in a fast-paced environment that requires strong technical and business judgment and solid communication skills. About the team Amazon CloudWatch Logs is a core monitoring service used by millions of AWS customers. We move fast and have delivered remarkable products and features over the last few years to streamline how AWS customers troubleshoot their critical applications. Our mission is to be the most cost effective, integrated, fast, and secure logs management and analytics platform for AWS customers. We are a diverse group of product and engineering professionals that are passionate about delivering logging features that delight customers operating at any scale. 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. Utility Computing (UC) 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.

Amazon CloudWatch is the native AWS monitoring and observability service for cloud resources and applications. We are seeking a talented Senior Applied Scientist to develop next-generation scientific methods and infrastructure to support a core AWS business that delivers critical services to millions of customers operating at scale. This is a high visibility and high impact role that work on highly strategic projects in the AI/ML and Analytics space, will interact with all levels of AWS leadership. We are developing solutions that not only surface the “what” but also the “why” and “how to fix it”, without requiring operators to have extensive domain knowledge and technical expertise to efficiently troubleshoot and remediate incidents. Using decades of AWS operational excellence coupled with the advances in LLMs and Gen-AI technologies, we are transforming the very core of how customers can effortlessly interact with our offerings to build and operate their applications in the cloud. We are hiring to grow our team, and are looking for well-rounded applied scientists with backgrounds in machine learning, foundation models, and natural language processing. You'll be working with talented scientists, engineers, and product managers to innovate on behalf of our customers. If you're fired up about being part of a dynamic, mission driven team, then this is your moment to join us on this exciting journey! Key job responsibilities As a Sr. Applied Scientist you will be responsible for * Research and development of algorithms that improve training of foundation models across pre-training, multitask learning, supervised finetuning, and reinforcement learning from human feedback * Research and development of novel approaches for anomaly detection, root cause analysis, and provide intelligent insights from vast amounts of monitoring and observability data * Collaborating with scientists, engineers, and Product Managers across CloudWatch team as well as directly with customers * Lead key science initiatives in strategic investment areas of AI/ML/LLM Ops and Observability * Be an industry thought leader representing Amazon at top-tier scientific conferences * Engaging in the hiring process and developing, growing, and mentoring junior scientists A day in the life Working closely with and across agile teams, you will be able to see and feel the impact of your work on our customers. This is a high visibility and high impact role that will interact with all levels of AWS leadership. Our ideal candidate is excited about the incredible opportunity that cloud monitoring represents and is deeply passionate about delivering the highest quality services leveraging AI/ML/LLMs. You’re naturally customer centric and thrive in a fast-paced environment that requires strong technical and business judgment and solid communication skills. About the team Amazon CloudWatch Logs is a core monitoring service used by millions of AWS customers. We move fast and have delivered remarkable products and features over the last few years to streamline how AWS customers troubleshoot their critical applications. Our mission is to be the most cost effective, integrated, fast, and secure logs management and analytics platform for AWS customers. We are a diverse group of product and engineering professionals that are passionate about delivering logging features that delight customers operating at any scale. 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. Utility Computing (UC) 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.

At Prime Video we are inventing a customer-centric future that offers more choice and flexibility than traditional Cable, Satellite television and other streaming providers. Where you can watch video content such as Prime Originals (Fallout, The Boys, The Marvelous Mrs. Maisel), movies, TV shows, Live sports (Thursday Night Football, English Premier League), local programming and hundreds of add-on subscriptions such as HBO max and Paramount+, anytime anywhere. All on your terms instead of having to pay for an expensive one-size-fits-all bundled package or be locked into long term contracts. The Core Playback organization operates at a global scale and is a critical part of Prime Video’s flywheel. We own Prime Video's core streaming technology and playback experience across all devices including Android phones and tablets, iOS devices, Web, Living Room Smart TVs, set top boxes, Windows10, Mac OSX, gaming consoles in more than 200 countries and territories. The technology landscape in streaming playback is rapidly changing. The Principal Scientist role in Core Playback reports to the Director of the organization with the intention of steering our science strategy across a wide range of areas. Key job responsibilities As a Principal Applied Scientist in the Prime Video Core Playback organization you will have deep subject matter expertise in applied machine learning. You will work with multiple teams of scientists, engineers and product managers to translate business and functional requirements into concrete deliverables. The field of Artificial Intelligence and Machine learning is experiencing unprecedented innovation and while it is important to know how recent advancements, such as GenAI, can be applied to develop new approaches to improve customer, developer and business outcomes, you'll work backwards from the desired outcomes to determine which ML technique is best applicable (traditional ML, GenAI, etc). Problem spaces you will be working on include: improving the customer streaming experience, video streaming and delivery heuristics in the PV apps, generating actionable insights from large scale of playback telemetry data, reducing the cost/effort/time to detect defects in customer's playback Quality of Experience (QoE) , applying ML to all aspects of the software development process to allow us to develop and release features faster and improving streaming playback quality and reliability. You will also work with external academic partners to support our in-house talent with direct access to cutting edge research and mentoring.