Careers

Amazon's Optimal Inventory Health (OIH) org in Supply Chain Optimization (SCOT) group is looking for a Principal Applied Scientist to optimize one of the most complex eCommerce systems in the world. The Optimal Inventory Health (OIH) drives long-term cash flow (LTFCF) growth by determining optimal inventory dispositions under uncertainties in demand, pricing, and supply across Amazon’s 21 marketplaces global network. OIH is in the unique position within SCOT to drive the joint optimization across supply chain and marketing across the levers of Markdowns, Removals, Outlet, Deals, Sponsored Ads, and Paid Search etc. Our systems deliver hundreds of million dollars saving to Amazon each year. The Principal Applied Scientist will lead the transformation from optimization-based model to Machine Learning/Reinforcement learning based decision-making models to optimize across inventory disposition channels and deliver best experience to Amazon customers through those levers. The role requires multidisciplinary skill sets across Reinforcement learning, Deep Learning Prediction, and Causal Inference et cetera. Academic and/or practical background in Transformer Architecture and Deep Reinforcement Learning are particularly relevant for this position. This position requires drive and self-motivation, superior analytical thinking, data-driven disposition, application of technical knowledge to a business context, effective collaboration with fellow scientists, software development engineers, and product managers, effective communication of technical designs to technical and non-technical audiences, and close partnership with many stakeholders from operations, finance, IT, and business leadership. Key job responsibilities - Seek to understand in depth the end to end value chain of eCommerce across supply chain and marketing and identify areas of opportunities to grow our business using science solutions. - Lead science strategy and roadmap in OIH space - Drive alignment across organizations to achieve business goals - Lead/guide scientists and engineers across teams to develop, test, launch and improve of science models designed to optimize inventory value and customer experience. - Be responsible for communicating our innovations to the broader internal & external scientific community and business leadership. - Mentor and guide the applied scientists in our organization and hold us to a high standard of technical rigor and excellence in ML. A day in the life - You will engage with distinguished scientists and Senior Principal scientists across organizations to shape the vision of the eCommerce decision systems across supply chain and marketing. - Our machine learning infrastructure built by talented engineering team (feature stores, template based ML pipelines and integration with experiment and production systems) will enable you to quickly prototype and iterate your innovative ideas. - You will collaborate with talented product managers and software engineers to build the end-to-end systems. - You will work with stakeholders across retail, supply chain, finance etc. to understand the business operation process and bottlenecks and build solution to provide the best experience to Amazon customers through automated OIH actions. About the team Supply Chain Optimization Technology (SCOT) is the core of the Amazon eCommerce business, which leverage science models and systems to automate the decisions and operations of the most complex supply chain in the world. Optimal Inventory Health (OIH) maximize the inventory value in Amazon through all the levers across traffic, marketing, pricing and reverse logistics.

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced algorithmic systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning and Data Sciences team for India Consumer Businesses. If you have an entrepreneurial spirit, know how to deliver, love to work with data, are deeply technical, highly innovative and long for the opportunity to build solutions to challenging problems that directly impact the company's bottom-line, we want to talk to you. Major responsibilities - Use machine learning and analytical techniques to create scalable solutions for business problems - Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes - Design, development, evaluate and deploy innovative and highly scalable models for predictive learning - Research and implement novel machine learning and statistical approaches - Work closely with software engineering teams to drive real-time model implementations and new feature creations - Work closely with business owners and operations staff to optimize various business operations - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation - Mentor other scientists and engineers in the use of ML techniques

The Bedrock AI Data Team in Amazon Web Services (AWS) is looking for a Language Engineer to collaborate in developing solutions for natural language data collections. This position is an opportunity to apply your expertise in a challenging but supportive environment. We are open to hiring candidates to work out of one of the following locations: The mission of the Bedrock AI Data Team is to engineer the datasets critical to the success of AWS’s Bedrock services. From human evaluations to Responsible AI safeguards to Retrieval-Augmented Generation and beyond, these products make Generative AI enterprise-ready and safe for users, impacting millions of people every day. We are a group of language engineers, linguists, data scientists, data engineers, and program managers, and we partner closely with the science, engineering, and product teams. We are customer obsessed and committed to delivering results with the highest quality and integrity. As a Language Engineer, you will start by diving deep into a couple of critical projects for Bedrock services to drive these projects forward. You will collaborate with fellow language engineers, program managers, as well as stakeholders in science, engineering, and product teams to understand the role data plays in developing models that meet customer needs. You will analyze, follow, and improve processes for collecting and annotating LLM inputs and outputs, assessing data quality, and automating where appropriate. You will then expand your scope by using the principles of data-centric AI to understand the role our data plays with regard to model performance specifically, as well as the larger ML pipeline. You will apply state-of-the-art Generative AI techniques to analyze how well our data represents human language and run experiments to gauge downstream interactions. You will work collaboratively with other language engineers and scientists to design and implement principled strategies for data optimization. Locations include Seattle, WA, USA | Santa Clara, CA, USA | New York City, NY, USA Key job responsibilities - Source, validate, and deliver high-quality language artifacts and linguistic data - Collaborate with stakeholders to design data collection and development efforts - Oversee the progress and quality of several data collection and annotation projects at a time - Advocate for strict adherence to data collection guidelines and quality thresholds - Extend existing data collection, annotation, and quality assurance efforts to support feature and language expansion - Innovate on data collection methodologies, guidelines, quality metrics to support new requests - Automate repetitive workflows and improve existing processes A day in the life The Bedrock AI Data Team at AWS is responsible for delivering high-quality annotated data and a variety of language artifacts to ensure the best performance of different AWS LLM services. These Generative AI services enable customers to readily add intelligence to their business operations and AI applications to drive positive outcomes. About the team AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.

We are seeking a Principal Applied Scientist to join our industry-leading team developing cutting-edge technologies in multi-robot planning and control. This is a unique opportunity to play a pivotal role in enabling fleets of autonomous mobile robots to operate safely and efficiently around humans in dynamic real-world environments. In this position, you will lead projects to push the boundaries of collaborative autonomy - getting teams of robots to cooperate and coordinate to get work done. You will develop and deploy new planning, coordination and control methods for our next generation of mobile robots. Your solutions will allow packs of robots to navigate warehouses transporting goods, performing services, and taking over dangerous dull dirty tasks - all while safely sharing space with people. This opportunity offers the chance to have broad impact by enabling robots to take on new roles that will transform how we work. You will collaborate with brilliant colleagues in a culture that values ingenuity, teamwork and making an impact. Come join our mission to pioneer the future of automation! About the team The Movement Science team studies algorithms for efficient motion planning and coordination of Amazon's mobile robots. Our aim is to improve the efficiency of robot movement and to enable adaptation to new operating conditions. We focus on two key requirements of movement: preserving liveness and working at scale. We are driven by system-level problems, where a new algorithm can unlock a new solution design, fix a significant shortcoming, guarantee performance under varying conditions, or improve how complex tradeoffs are made. As a science team, we take on projects which require cutting-edge research, a longer time-horizon, or carry significant risk.

Amazon Publisher Cloud is a game-changing new service, currently in beta, that operates at the intersection of advertising, secure signal collaboration, and cloud services. In this role you will be a key member of an entrepreneurial team tackling some of the most exciting and complex opportunities in digital advertising. Amidst rapid growth and evolving challenges, Amazon Publisher Cloud seeks a Principal Scientist with a deep passion for data, innovation, and the drive to explore new frontiers. This role is perfect for a leader capable of inspiring our team, pioneering cutting-edge strategies, and playing a crucial role in crafting world-class advertising solutions. If you're ready to lead in a culture that prioritizes experimentation, teamwork, and ownership, join us. Together, we'll lead the advancement of advertising, pushing boundaries to ensure our continued success and growth. Key job responsibilities As a Principal Applied Scientist in the team, you will: - Deeply analyze our current offerings to uncover opportunities for business growth through advanced ML solutions. - Provide mentorship to applied scientists and data scientists within the organization, setting a high bar for technical rigor and ML excellence. - Collaborate closely with engineering teams, leveraging your expertise to navigate technical constraints and achieve optimal performance. - Explore and pioneer innovative, high-impact research avenues in uncharted technical and scientific areas, leading them from inception to successful implementation. - Take the lead in sharing our ML breakthroughs with the wider scientific community and external stakeholders. - Research, build, and deploy innovative ML solutions; working across all technical disciplines. About the team Amazon Publisher Services helps digital publishers around the world build and grow thriving businesses. We provide services and advanced technologies to web, mobile app and advanced TV publishers of all sizes, including many of comScore’s global top 100, to help them monetize their content with demand from multiple programmatic buyers. Our server-side header bidding solutions are fast and reliable across devices, handling billions of queries per day, delivering ads in milliseconds. The result is more profitable advertising for publishers and more relevant ads for customers.


How can we improve the shopping experience on Amazon.com by tailoring what we display on our pages based on customer interests and preferences? How do we use generative models to help us innovate in different ways to enhance the shopping experience? How do we generate personalized content that helps customers shop at scale? Our team's stated missions is to "grow each customer’s relationship with Amazon by leveraging our deep understanding of them to provide relevant and timely product, program, and content recommendations." Recommendations at Amazon is a way to help customers discover products. Our team strives to better understand how customers shop on Amazon (and elsewhere) and build models that streamline customers' shopping experiences by showing the right products at the right time. Understanding the complexities of customers' shopping needs and helping them explore the depth and breadth of Amazon's catalog is a challenge we take on every day. Using Amazon’s large-scale computing resources, you will design and deploy state-of-the-art models that help customers shop on Amazon. You will ask research questions about customer behavior, design state-of-the-art models that help customers shop, and deploy these models to production. You will participate in the Amazon ML community and mentor Applied Scientists and software development engineers with a strong interest in and knowledge of ML and generative AI. Your work will directly benefit customers and the retail business. We are looking for a passionate, hard-working, and talented Applied Scientist who has experience developing state-of-the-art models and deploying them to production. You will have an opportunity to make an enormous impact on the design, architecture, and implementation of cutting edge products used everyday by people you know.

Amazon is looking for a talented Postdoctoral Scientist to join its AI Research on foundation models, large-scale representation learning, and distributed learning methods and systems for a one-year, full-time research position. At Amazon, you will invent, implement, and deploy state of the art machine learning algorithms and systems. You will build prototypes and innovate on new representation learning solutions. You will interact closely with our customers and with the academic and research communities. You will be at the heart of a growing and exciting focus area and work with other acclaimed engineers and world famous scientists. Large-scale foundation models have been the powerhouse in many of the recent advancements in computer vision, natural language processing, automatic speech recognition, recommendation systems, and time series modeling. Developing such models requires not only skillful modeling in individual modalities, but also understanding of how to synergistically combine them, and how to scale the modeling methods to learn with huge models and on large datasets. Join us to work as an integral part of a team that has diverse experiences in this space. We actively work on these areas: * Hardware-informed efficient model architecture, training objective and curriculum design * Distributed training, accelerated optimization methods * Continual learning, multi-task/meta learning * Reasoning, interactive learning, reinforcement learning * Robustness, privacy, model watermarking * Model compression, distillation, pruning, sparsification, quantization In this role, you will have the opportunity to: - Leverage machine learning models and advanced statistical techniques to extract valuable insights from historical data and comparable item information. - Tackle data scarcity challenges by developing innovative approaches to maximize the utility of available data sources. - Collaborate with cross-functional teams to develop and deploy production-ready solutions. - 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: • 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.

The Measurement, Ad Tech, and Data Science (MADS) team at Amazon Ads is at the forefront of developing cutting-edge solutions that help our tens of millions of advertisers understand the value of their ad spend while prioritizing customer privacy and measurement quality. We develop cutting-edge deterministic algorithms, machine learning models, causal models, and statistical approaches to empower advertisers with insights on the effectiveness of their ads in guiding customers from awareness to purchases. Our insights help advertisers build full-funnel advertising strategies. We maximize the information we extract from incomplete traffic signals and alternative sources to capture the impact of their ad spending for both Amazon recognized and anonymous traffic. Our vision is to lead the industry in extracting and combining information from several sources to enable advertisers to optimize their return on their ad spend. As an Applied Scientist on this team, you will: - Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. - 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. - 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. Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. Team video https://youtu.be/zD_6Lzw8raE Key job responsibilities * Lead the development of ad measurement models and solutions that address the full spectrum of an advertiser's investment, focusing on scalable and efficient methodologies. * Collaborate closely with cross-functional teams including engineering, product management, and business teams to define and implement measurement solutions. * Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop cutting-edge models that measure the impact of ad spend across multiple platforms and timescales. * Drive experimentation and the continuous improvement of ML models through iterative development, testing, and optimization. * Translate complex scientific challenges into clear and impactful solutions for business stakeholders. * Mentor and guide junior scientists, fostering a collaborative and high-performing team culture. * Foster collaborations between scientists to move faster, with broader impact. * Regularly engage with the broader scientific community with presentations, publications, and patents. A day in the life You will solve real-world problems by getting and analyzing large amounts of data, generate business insights and opportunities, design simulations and experiments, and develop statistical and ML models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the advertising organization. You will prepare written and verbal presentations to share insights to audiences of varying levels of technical sophistication. Team video https://advertising.amazon.com/help/G4LNN5YWHP6SM9TJ

Join us in the evolution of Amazon’s Seller business! The Selling Partner Recruitment and Success organization is the growth and development engine for our Store. Partnering with business, product, and engineering, we catalyze SP growth with comprehensive and accurate data, unique insights, and actionable recommendations and collaborate with WW SP facing teams to drive adoption and create feedback loops. We strongly believe that any motivated SP should be able to grow their businesses and reach their full potential by using our scaled, automated, and self-service tools. We aim to accelerate the growth of Sellers by providing tools and insights that enable them to make better and faster decisions at each step of selection management. To accomplish this, we offer intelligent insights that are both detailed and actionable, allowing Sellers to introduce new products and engage with customers effectively. We leverage extensive structured and unstructured data to generate science-based insights about their business. Furthermore, we provide personalized recommendations tailored to individual Sellers' business objectives in a user-friendly format. These insights and recommendations are integrated into our products, including Amazon Brand Analytics (ABA), Product Opportunity Explorer (OX), and Manage Your Growth (MYG). We are looking for a talented and passionate Principal Scientist to lead our research endeavors and develop world-class statistical and machine learning models. The successful candidate will work closely with Product Managers (PM), User Experience (UX) designers, engineering teams, and Seller Growth Consulting teams to provide actionable insights that drive improvements in Seller businesses. Key job responsibilities As a Principal Applied Scientist, you bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions.

The Central Science Team within Amazon’s People Experience and Technology org (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, well-being, and the value of work to Amazonians. We are an interdisciplinary team, which combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. We are looking for a Principal Economist who is able to provide structure around complex business problems, hone those complex problems into specific, scientific questions, and test those questions to generate insights. The ideal candidate will work with various science, engineering, operations, and analytics teams to estimate models and algorithms on large scale data, design pilots and measure their impact, and transform successful prototypes into improved policies and programs at scale. They will lead research projects to produce robust, objective research results and insights which can be communicated to a broad audience inside and outside of Amazon. Ideal candidates will work closely with business partners to develop science that solves the most important business challenges. They will work well in a team setting with individuals from diverse disciplines and backgrounds. They will serve as an ambassador for science and a scientific resource for business teams, so that scientific processes permeate throughout the HR organization to the benefit of Amazonians and Amazon. Ideal candidates will own the development of scientific models and manage the data analysis, modeling, and experimentation that is necessary for estimating and validating models. They will be customer-centric – clearly communicating scientific approaches and findings to business leaders, listening to and incorporate their feedback, and delivering successful scientific solutions.