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Careers

At Amazon, we believe that scientific innovation is essential to being the most customer-centric company in the world. Our scientists' ability to have an impact at scale allows us to attract some of the brightest minds across diverse fields including artificial intelligence, robotics, computer vision, economics, and sustainability. Join us in pioneering solutions to complex challenges that not only delight our customers but also help define the future of technology.
  • The program is designed for academics from universities around the globe who want to work on large-scale technical challenges while continuing to teach and conduct research at their universities.
  • The program offers recent PhD graduates an opportunity to advance research while working alongside experienced scientists with backgrounds in industry and academia.
  • Our internship roles span research areas to provide hands-on experience working alongside world-class scientists and engineers to advance the state of the art in your field.
695 results found
  • (Updated 5 days ago)
    We are seeking a Measurement and Attribution Analytics scientist to further the development and application of analytics methods to examine the complex data flows of measurement, attribution and shopper analytics and to translate deep-dives into actionable insights for our product teams. In this role you will develop new tools to analyze our advertising data to help improve the performance of our bidding algorithms, targeting and relevance systems, help advance our supply strategy, and evaluate the adoption and impact of feature releases. Key job responsibilities - Analyze data trends regarding supply, optimization, ad load, and advertising mix effects that affect advertiser performance and contribute to achieving advertiser goals. - Present papers to senior leaders on issues like feature development impact on identity recognition rates, and changes of ad selection systems to improve fill rate highlighting insights that will inform our business development and engineering roadmaps. - Identify, standardize, and operationalize KPIs to effectively measure the performance of all systems involved in ad serving, and use trend insights to inform business priorities. - Partner with engineering teams to define data logging requirements and getting these prioritized in engineering roadmaps. - Validate financial models through analysis - Develop and own ad revenue and supply intelligence analytics decks that provide ongoing deep-dives A day in the life The Measurement and Attribution Scientist will work closely with business leaders and engineers on developing common data architecture that will optimize our data logging at different grains, and will allow data interoperability from bid flow to optimization to campaign delivery. There will be an emphasis on understanding the impact of shopper journeys to and from Amazon properties and their implication on product development. The candidate will then analyze the data and present papers and ongoing reports on actionable insights. About the team The Ads Science Product Team's Mission: Work alongside those who need product data to apply objective perspective and business logic to uncover insights, advise strategic decisions, and adjust to industry changes.
  • US, NJ, Newark
    Job ID: 10559066
    (Updated 0 days ago)
    At Audible, we believe stories have the power to transform lives. It’s why we work with some of the world’s leading creators to produce and share audio storytelling with our millions of global listeners. We are dreamers and inventors who come from a wide range of backgrounds and experiences to empower and inspire each other. Imagine your future with us. ABOUT THIS ROLE We are seeking a data scientist builder to join the Audible economics team. Our group of economists, data scientists, and analysts tackles a wide range of questions, including pricing, experimentation science, data-driven product strategy/optimizations, internal productivity/incentives, audience science, and impact/ROI measurement. The ideal candidate will enjoy wearing many hats, possess an economist's mindset and a strong ability to effectively translate business questions into tractable quantitative frameworks, and excel at leveraging AI to build and scale robust, interpretable, and production-ready models/systems/tools. We're looking for someone who automates the repetitive, builds tools that force-multiply the team's output/influence, and treats AI as a core part of their workflow - not a side project. If you are passionate about leveraging data to shape the future of digital media, we encourage you to apply and be a part of our dynamic team. As a Data Scientist, you will... - Collaborate with economists, analysts, and other data scientists to build and scale econometric/ML models and quantitative tools - owning end-to-end scoping, data pipelining, feature engineering, model development/refinement, production-grade deployment, impact measurement, and adoption - Research and evaluate emerging tools and techniques (AI-driven and otherwise), and identify novel data sources to leverage in quantitative work – both from within Audible/Amazon and from 3P sources - Collaborate closely with Product, Content, and Marketing partners to drive broad impact and ensure that solutions are integrated into cross-functional workflows and executive decision-making - Represent the team in a range of settings - from reviews with senior Amazon scientists to reviews with senior Audible/Amazon business leaders - Mentor junior scientists and raise the bar for a new generation of scalable, AI-enabled science/analytical work, both within Audible and across the broader Amazon community ABOUT AUDIBLE Audible is the leading producer and provider of audio storytelling. We spark listeners’ imaginations, offering immersive, cinematic experiences full of inspiration and insight to enrich our customers daily lives. We are a global company with an entrepreneurial spirit. We are dreamers and inventors who are passionate about the positive impact Audible can make for our customers and our neighbors. This spirit courses throughout Audible, supporting a culture of creativity and inclusion built on our People Principles and our mission to build more equitable communities in the cities we call home. Key job responsibilities
  • US, WA, Seattle
    Job ID: 10539382
    (Updated 5 days ago)
    About Sponsored Products and Brands The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. About our team The General Shopping Intelligence (GSI) team is a highly motivated, collaborative, and fun-loving group with a strong entrepreneurial spirit and bias for action. We provide advanced real-time machine learning services that connect shoppers with the right ads across all platforms and surfaces worldwide. Through deep understanding of both shoppers and products, we help shoppers discover new products they love, enable advertisers to reach their customers most efficiently, and help Amazon continuously innovate on behalf of all customers. We are seeking a motivated Applied Scientist who loves to innovate at the intersection of customer experience, deep learning, generative AI and high-scale machine learning systems. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. Key job responsibilities As an Applied Scientist, you will: * Leverage Generative AI and Large Language Models (LLMs) to mine complex behavioral data, deriving deep, actionable shopper insights that identify customer experience gaps and unlock new business opportunities. * Design and develop scalable machine learning and GenAI models focused on shopper intent and preference modeling, ensuring a rapid path from prototype to production. * Partner closely with engineering teams to architect and deploy end-to-end GenAI solutions into production, integrating advanced insights directly into real-time, customer-facing systems. * Drive the scalability, efficiency, and automation of large-scale model training and real-time inference systems, pioneering the LLM infrastructure required to support next-generation GenAI workloads at Amazon Ads scale. * Design and run rigorous A/B experiments to quantify the business and customer impact of GenAI-driven shopper insights, performing advanced statistical analysis to guide iterative production rollouts. * Conduct applied research in novel generative AI techniques (e.g., fine-tuning, RAG, agentic workflows) to optimize the shopper experience and drive performance across all aspects of the Sponsored Products and Brands business.
  • (Updated 5 days ago)
    As an Applied Scientist in Amazon Fullfilment Technology, you will lead the development of agentic systems to assist with operational decision making and orchestration. You will work building full agentic systems leveraging multi-agent orchestration, tool use, memory, and action execution. You will train LLMs using a combination of rejection sampling approaches, SFT, continual post-training, and Reinforcement Learning (RL). These systems are deployed to Amazon buildings, and you will also work on rigorous offline and online evaluations. Your work will leverage the latest LLMs to develop capabilities for agentic reasoning, coding and analytics. You will also lead research projects to tackle unsolved problems, mentor interns, and author academic papers to summarize your findings for external publication. Key job responsibilities - Generating training and preference data for specific use cases (reasoning trajectories, tool traces) - Reward modeling and policy optimization for LLMs: DPO, IPO, RLHF/RLAIF with PPO/GRPO, rejection sampling. - Supervised fine-tuning on step-by-step trajectories and tool-use traces - Verbal Reinforcement Learning and Continual Learning - RL for LLMs, Offline RL and off-policy evaluation - Agentic memory/state management; episodic and semantic memory; vector search; grounding with RAG. - Evaluation: developing decision quality metrics, scaling LLM-based evaluations. About the team Amazon Fulfillment Technologies (AFT) powers Amazon's global fulfillment network. We invent and deliver software, hardware, and data science solutions that orchestrate processes, robots, machines, and people. We harmonize the physical and virtual world so Amazon customers can get what they want, when they want it. Learn more about AFT: https://tinyurl.com/AFTOverview
  • (Updated 5 days ago)
    As an Applied Scientist in Amazon Fullfilment Technology, you will lead the development of agentic systems to assist with operational decision making and orchestration. You will work building full agentic systems leveraging multi-agent orchestration, tool use, memory, and action execution. You will train LLMs using a combination of rejection sampling approaches, SFT, continual post-training, and Reinforcement Learning (RL). These systems are deployed to Amazon buildings, and you will also work on rigorous offline and online evaluations. Your work will leverage the latest LLMs to develop capabilities for agentic reasoning, coding and analytics. You will also lead research projects to tackle unsolved problems, mentor interns, and author academic papers to summarize your findings for external publication. Key job responsibilities - Generating training and preference data for specific use cases (reasoning trajectories, tool traces) - Reward modeling and policy optimization for LLMs: DPO, IPO, RLHF/RLAIF with PPO/GRPO, rejection sampling. - Supervised fine-tuning on step-by-step trajectories and tool-use traces - Verbal Reinforcement Learning and Continual Learning - RL for LLMs, Offline RL and off-policy evaluation - Agentic memory/state management; episodic and semantic memory; vector search; grounding with RAG. - Evaluation: developing decision quality metrics, scaling LLM-based evaluations. About the team Amazon Fulfillment Technologies (AFT) powers Amazon's global fulfillment network. We invent and deliver software, hardware, and data science solutions that orchestrate processes, robots, machines, and people. We harmonize the physical and virtual world so Amazon customers can get what they want, when they want it. Learn more about AFT: https://tinyurl.com/AFTOverview
  • (Updated 5 days ago)
    Amazon Web Services (AWS) is the world leader in providing a highly reliable, scalable, low-cost infrastructure platform in the cloud that powers hundreds of thousands of businesses in 190 countries around the world! Passionate about building, owning and operating massively scalable systems? Want to make a billion-dollar impact? If so, we have an exciting opportunity for you. The AWS Managed Operations (MO) organization was founded in April 2023, with the objective to reduce operational load and toil through long-term engineering projects. MO is building the best-in-class engineering and operations team that will own the day-to-day operations for AWS Regions, improving the availability, reliability, latency, performance and efficiency to operate AWS regions. The AWS Managed Operations Intelligence (MOI) Team is looking for a Data Scientist to lead the research and thought leadership to drive our data and insight strategy for AWS. You will be expected to serve as a Full Stack Data Scientist. You will be responsible for driving data-driven transformation across the organization. In this role, you will be responsible for the end-to-end data science lifecycle, from data exploration, ETL, model development and data visualization. You will leverage a broad set of tools and technologies, including general analytical frameworks (Spark, Airflow, etc.), AI frameworks (Hugging Face, etc.) and various machine learning frameworks, to tackle complex business problems. Your analytics research will provide direction on the technology strategy of the Managed Operations organization. Your Decision Science artifacts will provide insights that inform AWS' Operations and Site Reliability Engineering teams. You will work on ambiguous and complex business and research science problems at scale, and you are comfortable working with cross-functional teams and systems. By working together on behalf of our customers, we are building the future one innovative product, service, and idea at a time. Are you ready to embrace the challenge? Come build the future with us. Key job responsibilities - Work with large and complex data sets to solve a wide array of challenging problems using different analytical approaches - Develop ML/AI models. Partner with software teams to productionalize these models. - Data Pipeline and Infrastructure: design and implementation of data pipelines - Metric Development and Monitoring: Define and develop advanced, customized metrics and key performance indicators (KPIs) that capture the nuances of the organization's strategic objectives and operational complexities. Continuously monitor and evaluate the performance of metrics A day in the life Why AWS? Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we're building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future. Diverse Experiences AWS 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 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 Infrastructure Services (AIS) AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we're the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we're looking for talented people who want to help. Inclusive Team Culture AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events create stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. 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 the team The Managed Operations Intelligence (MOI) Team helps AWS operate its services across the world. We help monitor AWS operations by providing insights and recommendations on AWS operations.
  • (Updated 2 days ago)
    As part of the AWS Applied AI Solutions organization, we have a vision to provide end user applications, leveraging Amazon's unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers' businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon's real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are easy to adopt and easy to use. The Team Join the next science revolution at AWS Life Sciences Applied AI Solutions, where you'll work alongside world-class scientists to build AI that transforms how therapeutics are discovered, developed, and brought to patients. We're out to revolutionize how medicines are discovered, developed, and brought to patients, powered by a new generation of AI. Our team tackles some of the hardest open problems at the intersection of frontier AI and life sciences. We apply biological foundation models, large language models, and agentic reasoning systems to life sciences problems, then put them into the hands of customers as applications and managed services they can fine-tune, tailor, and deploy on their own data. The science challenges are deep: how do you design agentic systems that reason correctly over complex biological, regulatory, and clinical logic? How do you enable customers to tailor foundation models to their proprietary data and get better outputs with less effort? How do you adapt models to reason faithfully in high-stakes scientific and regulatory domains? Today we're focused on two areas. In clinical trials, we're building AI that automates and optimizes regulatory and clinical development workflows. In drug design, our products (including Amazon Bio Discovery) accelerate discovery by giving bench scientists AI-guided protein engineering and antibody design capabilities. We combine frontier research with production-scale delivery to put breakthrough science into the hands of customers solving humanity's hardest problems. We value scientific rigor, encourage publication, and support conference participation. If you want to do research that ships, this is the team. The Role We are seeking an Applied Scientist to build the models and methods behind our life sciences AI products, with a primary focus on clinical trial operations and agentic reasoning. You will design, train, and evaluate systems that reason over complex clinical and operational logic, and ship them into products customers use directly. You will work closely with senior and principal scientists on well-scoped research problems, own your results end to end, and see your work reach production. This role combines expertise in LLM reasoning and agentic AI with applied impact in life sciences. You will work on how large language models reason, plan, and act in complex scientific domains, while applying domain knowledge to ensure models produce scientifically valid outputs. The problems span multiple fronts: - How do you build LLM-based agentic systems that correctly reason over clinical protocols, regulatory standards, and complex multi-step operational workflows? - How do you evaluate agent reliability and faithfulness rigorously enough to trust in high-stakes clinical settings? - How do you develop model customization methods (fine-tuning, retrieval augmentation, domain adaptation) that let customers get strong results from foundation models on their own data? You will focus on clinical trial operations (agentic automation, structured reasoning, evaluation, domain adaptation), with opportunities to contribute across drug discovery (protein engineering, antibody design) as the portfolio grows. You will own end-to-end scientific solutions from research through production, and your work will directly shape the tools that scientists use daily. Key job responsibilities - Design, train, fine-tune, and evaluate LLM-based agentic systems that reason over clinical protocols, regulatory standards, and operational workflows - Build rigorous evaluation harnesses and benchmarks to measure agent reliability, faithfulness, and failure modes in high-stakes domains - Develop model customization methods (fine-tuning, RLHF, retrieval augmentation, domain adaptation) that help customers get better outputs on their own data with less effort - Contribute to graph-based and causal modeling approaches for clinical trial operations - Partner with Life Sciences domain experts, product, and engineering to translate scientific challenges into shipped capabilities - Own experiments end to end: problem framing, implementation, evaluation, iteration, and hand-off to production - Publish at top-tier venues where the work supports it - Contribute to drug discovery efforts (protein engineering, antibody design) as opportunities arise A day in the life - Design and run an experiment to validate a new agentic reasoning or fine-tuning method, then ship it as a capability customers can use - Diagnose why a model is failing on a new class of inputs and implement a fix to unblock a delivery milestone - Build or extend an evaluation benchmark to measure how faithfully an agent reasons over clinical logic - Meet with domain experts to scope what the next model release needs to do - Review results with a senior scientist, sharpen the approach, and get it over the finish line - Prototype a new idea that could become the next capability in the product About the team AWS Solutions As part of the AWS solutions organization, we have a vision to provide business applications, leveraging Amazon's unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers' businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. we blend vision with curiosity and Amazon's real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use. Diverse Experiences AWS 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. 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 AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. 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.
  • (Updated 6 days ago)
    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! This position involves research into and development of advanced DL models for video assets in order to improve their visual quality to be appealing to our customers (e.g. restoration from various defects, improving resolution, restoring truer colors, SDR->HDR up-conversion, better dithering/noising techniques to withstand compression artifacts, etc.). You will also develop next-generation methods for content-adaptive video encoding. You will work closely with subject matter experts (Research Scientists) with depth in the video encoding/quality/processing areas to maximize the video quality that Prime Video customers experience under a given network condition. Your work would directly influence the customer experience making Prime Video the destination for consuming content at the highest quality. Key job responsibilities The work would involve working with creation of ground-truth datasets, creating new video diffusion model architectures and training methodologies that ensure the best temporal consistency, preservation of creative intent, and perceptual quality. You will also work on optimization and deployment of such models in production workflow and will define/measure suitable at-scale success criteria. Aspects of work can involve scene understanding at a semantic level using latest techniques. You would develop innovative solutions that achieve the best balance between speed vs performance, file invention disclosures, and publish these novel approaches in tier-1 conferences. You would collaborate with research scientists with domain depth in video encoding/compression. You would conduct subjective ratings tests to generate ground truth data for your models, when required. You would also contribute to development of new video quality models that correlate highly with subjective ratings and help quantify the improvements brought about by your work. You would define and refine team processes around ML/DL model development, deployment, and guardrail definition. A day in the life You will work with Video Research Scientists who will bring domain expertise to jointly define the specific problem and technical approach. You may collaborate with academia through sponsored research programs on complex problems of long-term importance in your area of work. You will interface with ML engineers to convert your output into production workflows. You will help develop new AI workflows that are more efficient from a compute perspective. You will work with product managers to develop product roadmap that align with business goals. You will help hire new talent and will help develop talent through knowledge sharing and mentorship.
  • US, WA, Seattle
    Job ID: 10541930
    (Updated 5 days ago)
    AWS Applied AI Solutions (AAIS) is where science meets customer obsession at scale. We build the intelligent systems that power AWS services used by millions, combining research in machine learning, agentic AI, and applied science with the operational rigor required to deliver enterprise grade experiences. Within AAIS, Amazon WorkSpaces is our cloud based virtual desktop service that delivers secure, managed computing to over one million daily users across the globe, enabling organizations to provision, manage, and scale desktops with the reliability and performance their workforce depends on. We are looking for an Applied Scientist to be part of the tiger team building the capacity modelling for Amazon WorkSpaces, owning and advancing the science behind it. You will design, build, and continuously improve the forecasting and optimization models that ensure the right compute, storage, and networking resources are available at the right time, in the right regions, at the lowest possible cost, without ever compromising the end user experience. This is a high impact individual contributor role for someone who thrives at the intersection of applied research and production systems. You will define the scientific roadmap for capacity intelligence, turning reactive provisioning into a predictive, self optimizing engine that anticipates demand before customers feel any constraint. Key job responsibilities Define and drive the scientific strategy for capacity modelling, establishing the research agenda that transforms how WorkSpaces forecasts demand, plans supply, and allocates resources across a globally distributed infrastructure. Build advanced demand forecasting models that predict workspace usage across multiple time horizons, from intraday spikes to long range growth trajectories, incorporating signals such as customer onboarding patterns, seasonal trends, regional expansion, and macroeconomic indicators. Design supply optimization frameworks that determine optimal resource placement, instance mix, and pre warming strategies, balancing availability, performance, and cost by reasoning over hardware constraints, pricing dynamics, and service level objectives. Develop causal and probabilistic models that move beyond trend extrapolation to true understanding of demand drivers, enabling the organization to distinguish organic growth from one time events, anticipate shifts in usage patterns, and quantify uncertainty in planning decisions. Architect simulation and scenario planning systems that allow business and engineering leaders to run what if analyses, stress test capacity plans against disruption scenarios, and evaluate trade offs between investment timing, risk tolerance, and customer experience. Pioneer the integration of machine learning with operations research, combining deep learning based forecasting with mathematical optimization to jointly solve the demand prediction and resource allocation problem in a way that neither discipline can achieve alone. Establish evaluation frameworks and monitoring systems that measure forecast accuracy, capacity utilization, and cost efficiency in production, creating tight feedback loops that drive continuous model improvement and build organizational trust in science driven planning. Influence the broader organization's capacity strategy by translating model outputs into actionable recommendations for leadership, identifying opportunities to extend capacity intelligence patterns to adjacent services, and mentoring scientists and engineers across the team. About the team As part of the AWS solutions organization, we have a vision to provide business applications, leveraging Amazon's unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers' businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. we blend vision with curiosity and Amazon's real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use. Diverse Experiences AWS 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. 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 AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. 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.
  • (Updated 9 days ago)
    As part of the AWS Applied AI Solutions organization, we have a vision to provide end user applications, leveraging Amazon's unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers' businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon's real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are easy to adopt and easy to use. The Team Join the next science revolution at AWS Life Sciences Applied AI Solutions, where you'll work alongside world-class scientists to build AI that transforms how therapeutics are discovered, developed, and brought to patients. We're out to revolutionize how medicines are discovered, developed, and brought to patients, powered by a new generation of AI. Our team tackles some of the hardest open problems at the intersection of frontier AI and life sciences. We apply biological foundation models, large language models, and agentic reasoning systems to life sciences problems, then put them into the hands of pharma, biotech, and diagnostics customers as applications and managed services they can fine-tune, tailor, and deploy on their own data. The science challenges are deep: how do you design agentic systems that reason correctly over complex biological, regulatory, and clinical logic? How do you enable customers to tailor foundation models to their proprietary data and get better outputs with less effort? How do you adapt models to reason faithfully in high-stakes scientific and regulatory domains? Today we're focused on two areas. In drug design, our products (including Amazon Bio Discovery) accelerate discovery by giving bench scientists AI-guided protein engineering and antibody design capabilities. In clinical trials, we're building AI that automates and optimizes regulatory and clinical development workflows. We combine frontier research with production-scale delivery to put breakthrough science into the hands of customers solving humanity's hardest problems. We value scientific rigor, encourage publication, and support conference participation. If you want to do research that ships, this is the team. The Role We are seeking an exceptional Principal Applied Scientist to set the scientific direction for our life sciences AI portfolio. You will be the scientific leader who defines research agendas, architects novel approaches, and delivers models and methods that give our customers capabilities that did not previously exist. This is a rare role that combines deep expertise in LLM reasoning and agentic AI with applied impact in life sciences. You will innovate on how large language models reason, plan, and act in complex scientific domains, while applying domain knowledge in biology to ensure models produce scientifically valid outputs. The problems span multiple fronts: - How do you build LLM-based agentic systems that correctly reason over clinical protocols, regulatory standards, and complex multi-step scientific workflows? - How do you develop model customization and training methods that let customers get state-of-the-art results from foundation models? - How do you adapt and extend protein and antibody models so customers can fine-tune on proprietary sequence data and get therapeutically relevant outputs? You will work across drug discovery (protein engineering, antibody design) and clinical trial operations (agentic automation, structured reasoning, domain adaptation). You will own end-to-end scientific solutions from research through production, and your work will directly shape the tools that thousands of scientists use daily. Key job responsibilities - Set the scientific vision and research agenda for LLM reasoning, agentic AI, and biological model customization across the portfolio - Innovate on LLM reasoning, planning, and agentic approaches for complex scientific and regulatory workflows - Develop model customization methods (fine-tuning, RLHF, retrieval augmentation, domain adaptation) that enable customers to train better models on their own data with less effort - Advance methods to adapt and extend biological foundation models for customer-specific therapeutic applications - Solve open research problems in faithful reasoning, multi-step planning, and tool use in high-stakes scientific domains - Partner with Life Sciences domain experts and customers to understand their hardest scientific challenges and translate those into tractable research problems - Publish at top-tier venues and build the team's external scientific reputation - Mentor applied scientists across the team while maintaining significant personal research contribution - Collaborate with product and engineering to ensure research translates into shipped products that serve customers at scale - Influence multi-year research roadmaps through deep scientific expertise and customer understanding A day in the life - Push a new reasoning approach into production that measurably improves outputs for a pharma customer's workflow - Design and run experiments to validate a novel fine-tuning method, then ship it as a capability customers can use immediately - Unblock a delivery milestone by diagnosing why a model is failing on a new class of inputs and implementing a fix - Meet with a customer's scientific team to scope what the next model release needs to do for them - Review a teammate's experimental results, sharpen the approach, and help get it over the finish line - Publish results from shipped work at a top venue, closing the loop between research and impact - Prototype a new idea that could become the next major capability in the product

Science at Amazon around the world

Amazon scientists are working on large-scale technical challenges in a variety of research areas across the globe. Use the pins below to learn more about the customer-obsessed science being conducted at some of our research locations.
world map in greyscale
Australia
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New South Wales, AU
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Canada
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Ontario
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China
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Beijing, CN
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Germany
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India
Hyderabad, IN
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Bengaluru, IN
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Israel
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United States
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Academia

Amazon collaborates with leading academic organizations to drive innovation and to ensure that research is creating solutions whose benefits are shared broadly across all sectors of society.