Careers

The AWS Neuron Compiler team is actively seeking applied scientists to join our efforts in developing a state-of-the-art deep learning compiler stack. This stack is designed to optimize application models across diverse domains, including Large Language and Vision, originating from leading frameworks such as PyTorch, TensorFlow, and JAX. Your role will involve working closely with our custom-built Machine Learning accelerators, including Inferentia/Trainium, which represent the forefront of AWS innovation for advanced ML capabilities, powering solutions like Generative AI. The Automated Reasoning Group in the AWS Neuron Compiler team works on the intersection of Artificial Intelligence and program analysis to raise the code quality bar in compiler stack. In this role as an Applied Scientist, you'll be instrumental in designing, developing, and deploying analyzers for ML compiler stages and compiler IRs. You will contribute to the design and semantics of DSLs that our customers love when crafting neural architexctures. You will architect and implement business-critical tooling, publish cutting-edge research, and mentor a brilliant team of experienced scientists and engineers. You will need to be technically capable, credible, and curious in your own right as a trusted AWS Neuron engineer, innovating on behalf of our customers. Your responsibilities will involve tackling crucial challenges alongside a talented engineering team, contributing to leading-edge design and research in compiler technology and deep-learning systems software. Strong experience in programming languages, compilers, program analyzers, and program synthesis engines will be a benefit in this role. A background in machine learning and AI accelerators is preferred but not required. We expect a strong publication record in compilers, IR semantics, static analysis or verification. A day in the life 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. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.

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 Artificial Intelligence (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

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 algorithmic 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 and Data Sciences team for India Consumer Businesses. If you have an entrepreneurial spirit, know how to deliver, love to work with data, are deeply technical, highly innovative and long for the opportunity to build solutions to challenging problems that directly impact the company's bottom-line, we want to talk to you. Major responsibilities 3+ years of building machine learning models for business application experience PhD, or Master's degree and 2+ years of applied research experience Knowledge of programming languages such as C/C++, Python, Java or Perl Experience programming in Java, C++, Python or related language You have expertise in one of the applied science disciplines, such as machine learning, natural language processing, computer vision, Deep learning You are able to use reasonable assumptions, data, and customer requirements to solve problems. You initiate the design, development, execution, and implementation of smaller components with input and guidance from team members. You work with SDEs to deliver solutions into production to benefit customers or an area of the business. You assume responsibility for the code in your components. You write secure, stable, testable, maintainable code with minimal defects. You understand basic data structures, algorithms, model evaluation techniques, performance, and optimality tradeoffs. You follow engineering and scientific method best practices. You get your designs, models, and code reviewed. You test your code and models thoroughly You participate in team design, scoping and prioritization discussions. You are able to map a business goal to a scientific problem and map business metrics to technical metrics. You invent, refine and develop y

The Amazon Search team creates powerful, customer-focused search and advertising solutions and technologies. Whenever a customer visits an Amazon site worldwide and types in a query or browses through product categories, our services go to work. We design, develop, and deploy high performance, fault-tolerant distributed search systems used by millions of Amazon customers every day. This position will develop economic frameworks for selecting products into customer consideration sets, develop a theoretic framework of the search process and customer frictions that lends to policy evaluation, and create frameworks for coordinating product discovery with other marketplace decision systems like ordering, pricing, and delivery optimization. The ideal candidate will have outstanding Economics knowledge, demonstrated strength in practical and policy relevant structural econometrics, strong collaboration skills, proven ability to lead highly ambiguous and large projects, and a drive to deliver results. They will work closely with Economists, Data / Applied Scientists, Engineers, and Product leads to integrate economic insights into policy and production systems Familiarity with informational retrieval and recommender systems is a plus but not required. Key job responsibilities This role is responsible for creating mechanisms (metrics, models, mechanism) that optimize search while accounting for effects on the entirety of the Amazon Stores. Some example projects include: * Develop an economic frameworks for selecting products into customer consideration sets. Utilizing demand estimation, internalizing spillovers (e.g. menu effects), and incorporating long term effects on customer beliefs. We want to embed economics into state of the art list-wise ranking models. * Develop a means of valuing newly launched products and how the impact all aspects of the experience (prices, brand awareness, or even referential utility). * Develop a theoretic framework of the search process with a valuation of customer frictions that lends to evaluation of changes in the experience (aka a “search/browse model”) * Create frameworks for coordinating product discovery with other marketplace decision systems like ordering, pricing, and delivery optimization.

Are you interested in helping build a world-class transportation network for Amazon as we delight our customers with more 1 day promises and also meet our sustainability targets ? Do you want to deliver products at scale influence the network design of one of the most complex transportation network in the world? Amazon Worldwide Operations is looking for a Data Scientist. The role will require modeling, auditing and optimizing our transportation network from our fulfillment centers to our last mile carriers who deliver packages to customers. To be successful in the role, you need strong analytical skills, excellent communication skills, ability to influence across business functions and manage stakeholders’ expectations effectively. You will work in a fast-paced environment that requires you to be detail-oriented and comfortable in working with multiple business and technical teams. This position has the option to be located in Bellevue WA, Austin TX, Nashville TN, Santa Monica CA, Arlington VA, New York City NY, or Toronto CA. Key job responsibilities - Development of scalable data science solutions to audit and optimize our transportation network. - Development and execution of analytical tools to model our transportation network. - Contribute to the strategy for network design, prioritize technical and operational initiatives, evaluate and set stakeholders expectations.

The Machine Learning University (MLU) at Amazon drives the advancement of AI/ML adoption across the company. Our mission is to build a thriving community of AI/ML practitioners through comprehensive machine learning and generative AI training programs. We offer diverse technical tracks in generative AI, core ML techniques, and Deep Learning, while fostering innovation and best practices via showcasing AI advancements across Amazon. In light of the transformative advances in Generative and Agentic AI, we are seeking an Applied Scientist with expertise in these technologies and a proven track record of practical ML solutions. A key aspect of this role involves writing and maintaining reliable code that serves as the foundation for various AI projects and training programs across Amazon. You will need to stay continuously engaged with the rapidly evolving AI landscape, maintain strong connections with both internal and external ML experts, and effectively educate Amazon's technical and non-technical communities on these advances. The ideal candidate will excel at translating complex technical concepts into clear, actionable implementations and guidelines. You will develop practical code templates used by thousands of Amazon developers globally, share best practices in ML development, and collaborate with leading experts in GenAI, Deep Learning, and ML. This role demands both technical depth and breadth – from fundamental ML concepts to the latest GenAI developments – enabling you to guide others in implementing effective ML solutions. You'll create technical content, lead training sessions on ML best practices, and actively engage with Amazon's ML community. Your ability to clearly communicate complex AI concepts and emerging technologies will be crucial in helping teams across Amazon implement AI effectively. The position offers continuous opportunities to explore new AI technologies while connecting with diverse teams and enabling them to apply these advances in their work. Key job responsibilities - Design and maintain practical ML implementations and starter code templates that showcase best practices in Generative AI and ML, serving as foundational resources for Amazon teams globally. - Create and deliver technical training content focused on emerging AI technologies and ML best practices, adapting the material for both technical and business audiences across Amazon. - Collaborate with ML experts across Amazon to identify emerging AI/ML capabilities, ensuring our solutions align with the latest industry developments and internal needs. - Build and maintain connections with the broader AI/ML community through technical contributions, documentation, and knowledge sharing sessions. - Stay at the forefront of ML and Generative AI advancements, evaluating new technologies and methodologies for their practical applications within Amazon, and effectively communicating these insights to various teams. About the team The MLU team's strength lies in its diversity of backgrounds and experiences. Our team members come from varied career paths, bringing unique perspectives that enable us to tackle complex challenges in innovative ways. We actively seek builders from all backgrounds to join our team, and we encourage everyone to bring their authentic selves to work. This diversity of thought and experience consistently proves invaluable in solving challenging problems that would otherwise seem insurmountable. If you have both a technical foundation in AI/ML and a drive to help others succeed, join us in democratizing AI technology across Amazon!

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 Artificial Intelligence (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

The Postdoc for this role will research safety and efficiency aspects of generative AI for industries. From the safety perspective, the postdoc will research and present (internally and externally) a novel contribution to hallucination reduction, model/data/prompt safety or privacy-preserving training or fine-tuning methods with direct applications in one of our core industry segments. From the efficiency perspective, the postdoc will research and present a novel contribution to training, fine-tuning or operationalization methods that reduce cost, memory or carbon footprint of foundation models with a demonstration of its application in one of our core industry segments. Key job responsibilities This is a unique opportunity for a Postdoc to spearhead the effort to address safety and efficiency challenges behind adopting generative AI for Amazon's funded and ongoing industry product initiatives. This research will feed directly into Amazon's generative AI product strategies and features with industry customers and AIP segments. About the team The AWS Industry Products (AIP) team directly collaborates with strategic customers to build new, industry-specific products that directly impact and transform industries at AWS scale. We are a team of innovators that tackle difficult problems, and build products through fast iteration in a start-up like environment. AIP SCIFI team was formed to empower our customers to make better data-driven decisions by leveraging data science techniques such as ML and optimization.

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! As an Applied Science Manager in Machine Learning, you will: - Directly manage and lead a cross-functional team of Applied Scientists, Data Scientists, Economists, and Business Intelligence Engineers. - Develop and manage a research agenda that balances short term deliverables with measurable business impact as well as long term investments. - Lead marketplace design and development based on economic theory and data analysis. - Provide technical and scientific guidance to team members. - Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative and business judgment - Advance the team's engineering craftsmanship and drive continued scientific innovation as a thought leader and practitioner. - Develop science and engineering roadmaps, run annual planning, and foster cross-team collaboration to execute complex projects. - Perform hands-on data analysis, build machine-learning models, run regular A/B tests, and communicate the impact to senior management. - Collaborate with business and software teams across Amazon Ads. - Stay up to date with recent scientific publications relevant to the team. - Hire and develop top talent, provide technical and career development guidance to scientists and engineers within and across the organization. Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. Team video ~ https://youtu.be/zD_6Lzw8raE

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by preventing eCommerce fraud? Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms 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 enjoy collaborating in a diverse team environment? If yes, then you may be a great fit to join the Amazon Buyer Risk Prevention (BRP) Machine Learning group. We are looking for a talented scientist who is passionate to build advanced algorithmic systems that help manage safety of millions of transactions every day. Key job responsibilities Use machine learning and statistical techniques to create scalable risk management systems Learning and understanding large amounts of Amazon’s historical business data for specific instances of risk or broader risk trends Design, development and evaluation of highly innovative models for risk management Working closely with software engineering teams to drive real-time model implementations and new feature creations Working closely with operations staff to optimize risk management operations, Establishing scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation Tracking general business activity and providing clear, compelling management reporting on a regular basis Research and implement novel machine learning and statistical approaches