Careers

As a Principal Applied Scientist with Prime Video, you will be a senior thought leader in the group who finds new ways of applying state of art computer vision and language research to understand and manipulate video centric digital media - creating delightful outcomes for our customers. You will be responsible for creating a strong environment for applied science in order to recruit, retain and develop top talent. You will identify research directions, create roadmaps for forward-looking research and influence senior leadership on long-range investments in science.

Are you excited about developing foundation models to revolutionize automation, robotics and computer vision? Are you looking for opportunities to build and deploy them on real problems at truly vast scale? At Amazon Fulfillment Technologies and Robotics we are on a mission to build high-performance autonomous systems that perceive and act to further improve our world-class customer experience - at Amazon scale. We are looking for collaborative scientists, engineers and program managers for a variety of roles. The Amazon Robotics software team is seeking an experienced and senior Applied Scientist to focus on computer vision machine learning models. This includes building multi-viewpoint and time-series computer vision systems. It includes building large-scale models using data from many different tasks and scenes. This work spans from basic research such as cross domain training, to experimenting on prototype in the lab, to running wide-scale A/B tests on robots in our facilities. Key job responsibilities * Research vision - Where should we be focusing our efforts * Research delivery – Proving/dis-proving strategies in offline data or in the lab * Production studies - Insights from production data or ad-hoc experimentation. 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!

We are seeking an Economist to apply to help evaluate, and advance the science of, determining third-party seller fees and incentives. The working environment is collaborative and interdisciplinary. The successful candidate will: Leverage economic methods like modeling and impact estimation to address key issues using large, real-world datasets; Partner with PMs and BAs to identify data and define metrics evaluating business initiatives and making recommendations; Execute from idea to implementation as an integral part of cross-functional teams; Thrive in a highly complex and fast pacing environment. Key job responsibilities Build causal inference modeling to evaluate the effects of policy changes, such as fee adjustments and new fee structures, on seller behaviors and business metrics; Analyze how sellers and key outcomes are impacted by variations in growth strategies; Design experiments to measure pilot programs and support scaling-up effort; Synthesize learnings from past policy changes into critical insight to help the business develop new strategies and make science-based decisions. About the team The Seller Fees team owns the end-to-end fees experience for third-party sellers WW. We develop monetization strategies, Economics and Science models, and software that accurately charge Sellers fees while optimizing long-term Amazon growth; thereby allowing Sellers to offer Customers outstanding selection at sharp prices. Our systems let Amazon teams launch and change fees in ways that build Seller trust, ensuring every transaction is accurately calculated and transparent. The Fee domain includes Fee Strategy, Seller Experience, Seller Economics, ML, Data Science and Analytics, payments accuracy and integrity, and provides scalable technology to monetize Amazon’s services available to third-party sellers.

Amazon is looking for a talented Postdoctoral Scientist to join our Seller Fees Science & Tech team for a one-year, full-time research position. Postdoctoral Scientists will drive data-driven innovations in the seller fee domain for our EU marketplace. In this role, you will have the opportunity to: Leverage economic methods like modeling and impact estimation to address key issues using large, real-world datasets; Partner with PMs and BAs to identify data and define metrics evaluating business initiatives and making recommendations; Execute from idea to implementation as an integral part of cross-functional teams; Thrive in a highly complex and fast pacing environment. Participate in research activities, including publishing papers, attending conferences, and collaborating with academic institutions to advance the state-of-the-art in relevant fields. Key job responsibilities In this role you will: Build causal inference modeling to evaluate the effects of policy changes, such as fee adjustments and new fee structures, on seller behaviors and business metrics; Analyze how sellers and key outcomes are impacted by variations in growth strategies; Design experiments to measure pilot programs and support scaling-up effort; Synthesize learnings from past policy changes into critical insight to help the business develop new strategies and make science-based decisions. 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. Publish your innovation in top-tier academic venues and hone your presentation skills. Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise. About the team The Fee Science Team works on science, economic, machine learning, and data engineering projects for Selling Partner Services and third-party fees. Our projects include causal modeling and impact of structural changes, models that support fee integrity, business analytics, and a comprehensive set of data sources and pipelines.

Interested in helping build Prime's Machine Learning system to drive huge business impact on millions of customers? Join our team of Scientists developing algorithms to adaptively generate and experiment on new content, personalize, and optimize the Prime membership experience. This includes identifying building foundational models that serve as an abstraction of our high-dimensional customer data, understanding who our customers are, and providing them with personalized experiences. As an ML lead, you will partner directly with product owners to intake, build, and directly apply your modeling solutions. There are numerous scientific and technical challenges you will get to tackle in this role, such as deep learning techniques and natural language processing to abstract sequences and embeddings from customer features, offer/content features. These abstraction layers will then be used by our personalization, segmentation, and experimentation platforms. We employ techniques from deep learning, NLP, multi-armed bandits, optimization, and RL - while this role is focused on leading the cross-sectional space of deep learning, NLP, and RL. As the central science team within Prime, our expertise gets routinely called upon to weigh in on a variety of topics. We also emphasize the need and value of scientific research and have developed a strong publication and patent record (internally/externally) which you will be a part of. You will also utilize and be exposed to the latest in ML technologies and infrastructure: AWS technologies (EMR/Spark, Sagemaker, DynamoDB, S3, Andes, Bedrock ...), various ML algorithms and techniques (Random Forests, Neural Networks, supervised/unsupervised/semi-supervised/reinforcement learning, LLM's), and statistical modeling techniques. Major responsibilities: - Build and develop machine learning models and supporting infrastructure at TB scale, in coordination with software engineering teams. - Leverage Deep Learning, NLP, and Reinforcement Learning for our Optimization Systems. - Develop offline policy estimation tools and integrate with reporting systems. - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation. - Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes. - Work closely with the business to understand their problem space, identify the opportunities and formulate the problems. - Use machine learning, data mining, statistical techniques and others to create actionable, meaningful, and scalable solutions for the business problems. - Design, develop and evaluate highly innovative models and statistical approaches to understand and predict customer behavior and to solve business problems.

Amazon Web Services is looking for world class scientists to join the Security Innovation team in AWS Global Services Security (GSS). GSS is responsible for delivering product-led, people-powered services that help our customers operate their business securely on AWS, and we are accelerating our adoption of AI/ML. This is an exciting opportunity to contribute at the intersection of AI/ML, cloud, and cybersecurity. Your primary responsibility will be to envision, experiment, prototype, and mature to scale AI/ML solutions in our products to meet the needs of our customers. You will have the opportunity to work with multiple lines of business, and learn from (and contribute to) a variety of security use cases. This is a hands-on role where success is measured by producing solutions that have measurable impact. If you have experience with large scale machine learning and have a passion for security, this will be an exciting opportunity. Key job responsibilities * Collaborate with security and business teams to identify viable ML opportunities and develop a plan from experiments to proof-of-concept to software product. * Conduct cutting-edge research and deliver new initiatives with potential to impact multiple teams and customers in the medium to long term. * Invent, implement, and deploy state-of-the-art machine learning algorithms and systems for information security applications. * Lead collaboration with software engineering teams to integrate successful experiments into large-scale, highly complex production services. * Experiment and report results in a scientifically rigorous way. * Advance the state of the art through invention, patents, and external publications. * Define and lead a long term research agenda 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. About 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. 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.

About Amazon Health Amazon Health’s mission is to make it dramatically easier for customers to access the healthcare products and services they need to get and stay healthy. Towards this mission, we (Health Storefront and Shared Tech) are building the technology, products and services, that help customers find, buy, and engage with the healthcare solutions they need. Job summary We are seeking an exceptional Senior Applied Scientist to join a team of experts in the field of machine learning, and work together to break new ground in the world of healthcare to make personalized and empathetic care accessible, convenient, and cost-effective. We leverage and train state-of-the-art large-language-models (LLMs) and develop entirely new experiences to help customers find the right products and services to address their health needs. We work on machine learning problems for intent detection, dialogue systems, and information retrieval. You will work in a highly collaborative environment where you can pursue both near-term productization opportunities to make immediate, meaningful customer impacts while pursuing ambitious, long-term research. You will work on hard science problems that have not been solved before, conduct rapid prototyping to validate your hypothesis, and deploy your algorithmic ideas at scale. You will get the opportunity to pursue work that makes people's lives better and pushes the envelop of science. #everydaybetter Key job responsibilities - Translate product and CX requirements into science metrics and rigorous testing methodologies. - Invent and develop scalable methodologies to evaluate LLM outputs against metrics and guardrails. - Design and implement the best-in-class semantic retrieval system by creating high-quality knowledge base and optimizing embedding models and similarity measures. - Conduct tuning, training, and optimization of LLMs to achieve a compelling CX while reducing operational cost to be scalable. A day in the life In a fast-paced innovation environment, you work closely with product, UX, and business teams to understand customer's challenges. You translate product and business requirements into science problems. You dive deep into challenging science problems, enabling entirely new ML and LLM-driven customer experiences. You identify hypothesis and conduct rapid prototyping to learn quickly. You develop and deploy models at scale to pursue productizations. You mentor junior science team members and help influence our org in scientific best practices. About the team We are the Health AI team at HST (Health Store and Technology). The team consists of exceptional ML Scientists with diverse background in healthcare, robotics, customer analytics, and communication. We are committed to building and deploying the most advanced scientific capabilities and solutions for the products and services at Amazon Health.

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.

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!

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and innovative applied scientist with a strong background in responsible AI, deep learning and large language models (LLMs) techniques to develop and deploy world-class foundation models. Key job responsibilities As an Applied Scientist with the AGI team, you will work with world-class scientists and engineers to develop novel data, modeling and engineering solutions to support the responsible AI initiatives at AGI. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources and collaborate with colleagues cross-AGI to achieve this objective. Your work will have a direct impact to AGI's business and customers through the foundation models we develop and depoly. About the team Our team's mission is to develop and deploy industry-leading foundation models that set the benchmark for the industry, comply with the relevant responsible RAI policies and delight our customers in the process.