Careers

The Amazon Alexa AI team in India is seeking a talented, self-driven Applied Scientist to work on prototyping, optimizing, and deploying ML algorithms within the realm of Generative AI. Key responsibilities include: - Research, experiment and build Proof Of Concepts advancing the state of the art in AI & ML for GenAI. - Collaborate with cross-functional teams to architect and execute technically rigorous AI projects. - Thrive in dynamic environments, adapting quickly to evolving technical requirements and deadlines. - Engage in effective technical communication (written & spoken) with coordination across teams. - Conduct thorough documentation of algorithms, methodologies, and findings for transparency and reproducibility. - Publish research papers in internal and external venues of repute - Support on-call activities for critical issues

Take Earth's most customer-centric company. Mix in hundreds of millions of shoppers spending tens of billions of dollars annually, an exciting opportunity to build next-generation shopping experiences, Amazon’s tremendous computational resources, and our extensive e-Commerce experience. What do you get? The most exciting position in the industry. About our organization: Our team is part of Amazon’s Personalization organization, a high-performing group that leverages Amazon’s expertise in machine learning, big data, distributed systems, and user experience design to deliver the best shopping experiences for our customers. We run global experiments and our work has revolutionized e-commerce with features such as "Keep shopping for", "Tap to explore", “Customers who bought this item also bought”, and “Frequently bought together” among others. Amazon’s internal surveys regularly recognize us as one of the best engineering organizations to work for in the company, with visible high-impact work, low operational load, respectful work-life balance, and continual opportunity to learn and grow. You will play a critical role in ideation for the team. We are building the next generation ML systems that powers the biggest shopping engine on earth, and we hope you will join us! Key job responsibilities As an Applied Scientist on the team you will be working on cutting edge ways to help customers find the right products and content on their shopping journey. Our goal is to help customers achieve their objective seamlessly while shopping on Amazon. We are investing in multiple fronts including but not limited to GenerativeAI, LLMs, transformers, sequence models, reinforcement learning, MABs. This is an opportunity to come in on Day0 and influence the science roadmap of one of the most interesting problem spaces at Amazon - understanding the Amazon customer to build deeply personalized and adaptive shopping experiences. We will be working on applying cutting edge science and research into production to elevate the customer experience. You will be part of a multidisciplinary team, working on one of the largest scale machine learning systems in the company. You will hone your skills in areas such as deep learning and reinforcement learning while building scalable industrial systems. As a member of a highly leveraged team of talented engineers and ML scientists, you will have a unique opportunity to help build infrastructure that accesses petabytes of data to produce and deliver models that deliver state of the art customer experiences. About the team Our mission is to delight every Amazon customer with a consistent and adaptive personalized shopping experience. We achieve our mission through investments in large scale machine learning, distributed systems and user experience with the purpose of delivering the future of shopping on Amazon. We are seeking an Applied Scientist to work on step function science improvements to help achieve SOTA results and to help build new Personalization experiences for Amazon customers.

Amazon Web Services (AWS) is building a world-class marketing organization, and we are looking for an experienced Economist to join the central data and science organization for AWS Marketing. This candidate will develop innovative solutions to measure the return on marketing investments. They will work closely with business leaders, scientists, and engineers to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of innovative measurement solutions. They will interact with functional leaders owning events (e.g. re:Invent, summits, webinars), paid media (paid search, paid social, display), AWS-owned channels (email, website, console) as well as lead management organization to drive the development, fine-tuning and adoption of the consistent measurement framework across these diverse initiatives. We seek candidates with an entrepreneurial spirit who want to make a big impact on AWS growth. They will develop strong working relationships and thrive in a collaborative team environment. They will have the creativity, curiosity, and strong judgment to work on high-impact, high-visibility products to improve the experience of AWS leads and customers. Key job responsibilities - Apply your expertise in causal inference and ML to develop systems to measure B2B marketing impact - Develop and execute science products from concept, prototype to production incorporating feedback from customers, scientists and business leaders - Identify new opportunities for leveraging economic insights and models in the marketing space - Write technical white papers and business-facing documents to clearly explain complex technical concepts to audiences with diverse business/scientific backgrounds

Profit Intelligence (PI) team in Amazon , owning Amazon's core profitability prediction system, is looking for an ambitious Economist to build the next generation of profitability science for Amazon. As an Economist in PI, you will partner closely with senior management, business stakeholders, applied scientists and engineers, and economist leadership to solve key business problems that are at the core of economic prediction and cost optimization for Amazon, empowering downstream teams to make high-velocity, high-quality profitability decisions for both short term and long term. You will utilize massive data, state-of-the-art scientific computing, econometrics, time-series forecasting, and machine-learning, etc. to do so. Some of the science you create will be publishable in internal or external scientific journals and conferences. You will work closely with a team of economists, applied scientists, business analysts, data engineers, product managers, and software engineers. The team is unique in its exposure to company-wide strategies, and operates at the research frontier of utilizing data, econometrics, artificial intelligence, and machine-learning to inform business profitability strategies. Key job responsibilities A successful candidate will have demonstrated a capacity for building, estimating, and defending statistical models (e.g., time-series, machine-learning) using software such as R and Python. They will have a willingness to learn and apply a broad set of statistical and computational techniques to supplement deep-training in one area of econometrics. For example, many applications on the team rely on building scalable production software at Amazon data scale, which involves a broad set of world-class software-building skills often learned on-the-job. As a consequence, already-obtained knowledge of SQL, Python, machine learning, and large-scale scientific computing using distributed computing infrastructures such as Spark-Scala or PySpark would be a plus. Additionally, this candidate will show a track-record of delivering projects well and on-time, preferably in collaboration with other team members (e.g. co-authors). Candidates must have advanced experience writing and emotional intelligence skills (for collaborative teamwork, often with colleagues in different functional roles), a growth mindset, and a capacity for dealing with a high-level of ambiguity. Endowed with these traits and on-the-job-growth, the role will provide the opportunity to have a large strategic, world-wide impact on Amazon e-commerce business.

What does it take to build a foundation model that can forecast demand for hundreds of millions of products — including ones that have never been sold before? At Amazon, our Demand Forecasting team is tackling one of the most ambitious challenges in applied time series research: building large-scale foundation models that generalize across an enormous and diverse catalog of products, geographies, and business contexts. This is not incremental modeling work. We are redefining what's possible in demand forecasting. Our team operates at a scale that is unmatched in industry. We run experiments across millions of products simultaneously, pushing the boundaries of what foundation models can learn from vast, heterogeneous time series data. We are also exploring novel data generation techniques that augment our already unprecedented dataset — opening new frontiers in model generalization and forecasting for products with limited or no sales history. The models you build here will ship to production and directly influence hundreds of millions of dollars in automated inventory decisions every week, labor plans for tens of thousands of employees, and Amazon's financial outlook. Beyond operational impact, this team contributes to the broader scientific community and advances the state of the art in time series foundation models. If you are a scientist who wants to work at the frontier of time series research, at a scale no academic lab or startup can match, and see your work deployed to real-world impact — this is the team for you. Key job responsibilities - Design and run rigorous experiments at scale to evaluate and improve foundation model performance across hundreds of millions of products, geographies, and business verticals - Lead the end-to-end lifecycle of forecasting models — from research and experimentation through production launch — including defining success metrics, obtaining stakeholder sign-off, and managing rollout - Conduct online and offline labs to measure the real-world impact of forecast improvements beyond accuracy, including downstream supply chain, inventory, and financial outcomes - Develop and deploy production-grade deep learning and statistical models using Python, Scala, SQL, and related tools - Perform large-scale exploratory data analysis to uncover patterns, identify opportunities, and inform model development - Translate complex research findings into clear insights and recommendations for technical and non-technical stakeholders at all levels - Contribute to Amazon's scientific community and the broader research field through collaboration and publication in top-tier venues A day in the life No two days look the same, but most will involve some combination of deep technical work, cross-functional collaboration, and scientific thinking at a scale you won't find anywhere else. You might start the morning reviewing the results of an experiment running across hundreds of millions of products — analyzing whether a new foundation model variant is improving generalization on cold-start items, or whether a novel data generation approach is meaningfully shifting forecast quality. You'll dig into the numbers, form a hypothesis, and design the next iteration. Later in the day, you could be in a stakeholder review, walking business and engineering partners through a set of launch metrics — explaining not just forecast accuracy, but the downstream supply chain and financial impact your model is driving. Getting a model to production at Amazon requires rigor: you'll define success criteria, run online and offline labs to validate real-world impact, and build the case for sign-off across technical and business stakeholders. You'll write code — Python, Scala, SQL — to process and analyze data at a scale most scientists never encounter. You'll collaborate closely with scientists, engineers, and business teams, and contribute to research that has a real chance of being published and advancing the field. The work is hard, the problems are unsolved, and the impact is immediate. If you want to do research that ships — this is where you do it. About the team The Demand Forecasting team sits at the heart of Amazon's supply chain, building the science that determines what products are available, when, and at what cost — for hundreds of millions of customers around the world. Our mission is to push the frontier of what's possible in large-scale time series forecasting, and to deploy that science where it creates real, measurable impact. We are a team of scientists who care deeply about both research rigor and real-world outcomes. We don't just publish — we ship. And we don't just ship — we measure, iterate, and raise the bar. Our work spans the full lifecycle: from foundational research and large-scale experimentation to production deployment and downstream impact measurement across supply chain, inventory, and financial planning.

Join the Personal Robotics Group at Amazon, where you'll help pioneer intelligent robotic products that deliver meaningful customer experiences. As a Senior Applied Scientist, you'll drive technical excellence in robotic task planning, developing and improving algorithms that enable robots to learn and execute complex tasks in dynamic real-world environments, while establishing evaluation and benchmarking methodology to measure system performance. In this role, you will combine hands-on technical work with scientific rigor, researching and developing novel approaches to task planning and understanding, improving models to enhance performance, and designing experiments and benchmarks that drive measurable progress. You'll leverage Amazon's computational resources and robotics infrastructure to tackle ambitious challenges in areas such as task planning, task understanding, reasoning, and human-robot interaction. Key job responsibilities - Research and develop novel approaches to robotic task planning, task understanding, and reasoning to improve system performance - Design and implement evaluation frameworks and benchmarks for robotic planning systems, driving measurable improvements - Explore and fine-tune models to enhance robot capabilities across diverse tasks and environments - Build and maintain datasets and data collection pipelines for training and evaluating models - Define quantitative metrics and success criteria that connect evaluation results to real-world robot performance - Collaborate with engineering teams to integrate research findings and evaluation into development workflows - Partner with cross-functional teams to ensure holistic improvement of robot capabilities - Stay current with the latest advancements in robotics, task planning, and AI research A day in the life - Research and prototype new approaches to improve task planning and understanding capabilities - Design and run experiments to identify limitations of current approaches, documenting findings and proposing improvements - Fine-tune and iterate on models to improve performance across diverse scenarios - Build and iterate on evaluation pipelines that measure system quality and reliability About the team The Personal Robotics Group is pioneering intelligent robotic products that deliver meaningful customer experiences. We're building the next generation of robotic systems that will redefine how customers interact with technology. This is a unique opportunity to shape the future of personal robotics working with world-class teams pushing the boundaries of what's possible in robotic manipulation, locomotion, task planning, and human-robot interaction. Join us if you're passionate about creating the future of personal robotics, solving complex challenges at the intersection of hardware and software, and seeing your innovation deliver transformative customer experiences.

About Sponsored Products and Brands The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading 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 Amazon Brand Store team (such as www.amazon.com/lego) within Sponsored Products and Brands is a core product offering in the Amazon Advertising portfolio. The brand's store are their dedicated place on Amazon to differentiate, grow sales, and build loyalty with millions of shoppers. Our mission is to empower brands of all sizes to tell their story in their own unique voice to consumers. We help brands create engaging shopping experiences that assist shoppers in discovering and evaluating them as part of their purchase decisions. We succeed when we are both useful to shoppers and when brands can attract and retain shopper's attention using our products. A cool case study on brand stores can be found here: https://advertising.amazon.com/library/case-studies/nespresso-brand-store-increases-shopper-engagement. We are looking for a Senior Applied Scientist to lead the generation of data-driven insights that bring long-term value to brands, as well as the ideation and creation of personalized shopping experiences for deep business understanding. You will be expected to identify and solve ambiguous problems and science deficiencies, and to provide informed solutions based on state-of-the-art machine learning research. Impact and Career Growth You will invent new experiences and influence customer-facing shopping experiences to help brands grow their retail businesses. This is your opportunity to work within the fastest-growing businesses across all of Amazon! You'll define a long-term science vision for AI-driven brand shopping experiences, working backwards from our customers' needs and 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. Key job responsibilities As a Senior Applied Scientist on this team, you will: - Be the technical leader in Machine Learning; lead efforts within this team and across other teams. - Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience. - Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. - Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models. - Run A/B experiments, gather data, and perform statistical analysis. - Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. - Research new and innovative machine learning approaches. - Recruit Applied Scientists to the team and provide mentorship.

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! As an Applied Scientist in the Prime Video Playback Intelligence Organization, you will have deep subject matter expertise in applied machine learning and data science, with specializations in video streaming optimization, information retrieval, anomaly detection and root-causing systems, large language models and generative AI across various modalities. Key job responsibilities - Work with multiple teams of scientists, engineers, and product managers to translate business and functional requirements into concrete deliverables leading strategic efforts to enhance customer quality of experiences. - Work on problems spaces such as: improving the customer playback quality of experience across Video on Demand, Live Events and Linear Content. - Reduce the time/cost/effort to optimize the customer experience as well as detect, root-cause, and mitigate defects in the customer experience. You’ll seek to understand the depth and nuance of streaming video at scale and identify opportunities to grow our business and improve customer quality of experience via principled ML/AI solutions. - Lead integration of new algorithms and processes into existing modeling stacks, simplify and streamline the existing modeling stacks, and develop testing and evaluation strategies. Ultimately, you'll work backwards from the desired outcomes and lead the way on determining the ideal solution (statistical techniques, traditional ML, GenAI, etc). A day in the life We love solving challenging and hard problems in our quest to innovate on behalf of our customers and provide the best video streaming experience. We push the boundaries to leverage and invent technologies which help create unrivaled experiences for our customers to help us move fast in a growing and changing environment. We use data to guide our decisions, work closely with our engineering and product counterparts, and partner with other Science teams as well as academic institutions to learn and guide in an environment of innovation.

Selection Monitoring team is responsible for making the biggest catalog on the planet even bigger. In order to drive expansion of the Amazon catalog, we develop advanced ML/AI technologies to process billions of products and algorithmically find products not already sold on Amazon. We work with structured, semi-structured and Visually Rich Documents using deep learning, NLP and image processing. The role demands a high-performing and flexible candidate who can take responsibility for success of the system and drive solutions from research, prototype, design, coding and deployment. We are looking for Applied Scientists to tackle challenging problems in the areas of Information Extraction, Efficient crawling at internet scale, developing ML models for website comprehension and agents to take multi-step decisions. You should have depth and breadth of knowledge in text mining, information extraction from Visually Rich Documents, semi structured data (HTML) and advanced machine learning. You should also have programming and design skills to manipulate Semi-Structured and unstructured data and systems that work at internet scale. You will encounter many challenges, including: - Scale (build models to handle billions of pages), - Accuracy (requirements for precision and recall) - Speed (generate predictions for millions of new or changed pages with low latency) - Diversity (models need to work across different languages, market places and data sources) You will help us to - Build a scalable system which can algorithmically extract information from world wide web. - Intelligently cluster web pages, segment and classify regions, extract relevant information and structure the data available on semi-structured web. - Build systems that will use existing Knowledge Base to perform open information extraction at scale from visually rich documents. Key job responsibilities - Use AI, NLP and advances in LLMs/SLMs and agentic systems to create scalable solutions for business problems. - Efficiently Crawl web, Automate extraction of relevant information from large amounts of Visually Rich Documents and optimize key processes. - Design, develop, evaluate and deploy, innovative and highly scalable ML models, esp. leveraging latest advances in RL-based fine tuning methods like DPO, GRPO etc. - Work closely with software engineering teams to drive real-time model implementations. - Establish scalable, efficient, automated processes for large scale model development, model validation and model maintenance. - Lead projects and mentor other scientists, engineers in the use of ML techniques. - Publish innovation in research forums.

About us As part of the AWS Applied AI Solutions organization, our vision is 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. Our team combines Amazon's real-world experience with state-of-art AI to create opinionated, turnkey solutions that are no-brainers to buy and easy to use. We're building applied AI solutions that businesses love and trust. Our ambition is to become the partner companies rely on to run their business every day—putting AI to work to deliver better customer experiences, operational excellence, and faster innovation. We're a fast-moving, scrappy team building a new agentic product from the ground up. If bias for action is your favorite leadership principle, you'll fit right in. The Role We're seeking a talented Applied Scientist with expertise in large language models, agentic systems, and foundational models. You will be responsible for building the state-of-art multi-agent system, using a handful of methods including fine-tunning, reinforcement learning, etc. You'll accelerate our customer-facing features, contribute to our collaborative and innovative culture, and bring state-of-art applied research that raises the bar for the entire team. Key job responsibilities • Drive end-to-end GenAI projects with high complexity and ambiguity from conception to production • Build, optimize, and deploy ML models while collaborating with software engineers for productionization • Research innovative machine learning approaches and identify new opportunities for GenAI applications • Perform hands-on analysis and modeling of large datasets to develop actionable insights • Establish scalable, automated processes for data analysis, model development, and validation • Present results to senior leadership and collaborate with cross-functional teams About the team 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.