Careers

Amazon is looking for talented Postdoctoral Scientists to join our Forward Looking Initiatives & Technology Enablers (FLITE) Team for a one-year, full-time research position. The Forward Looking Initiatives & Technology Enablers (FLITE) Team. FLITE’s charter is to enable Amazon Robotics Manipulation Organization to innovate on advanced technology development. The research work for this position will explore generalization of grasp policies in simulation and on novel hardware platforms. The Postdoc will research, propose, and develop policies by leveraging the state-of-the-art visuomotor polices, data-efficient reinforcement learning methods, and foundation models for robotic perception and manipulation. The candidate will prototype algorithms in simulation and then deploy promising solutions to real and novel hardware. They will provide direction on where we should be focusing our efforts in this rapidly developing field and innovate and iterate on deep learning solutions for robotic manipulation. Key job responsibilities • 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.

Are you excited by the idea of inventing new experiences on the most visited shopping page - amazon.com? Can you imagine saving millions of shoppers' time worldwide by presenting them with compelling products, services, and offers on Amazon homepage and product detail pages? Are you looking forward to solving challenging problems that blend business, scientific, and engineering disciplines? We work with billions of products and measure our impact in $'00 millions. Join us, be part of the shopping revolution, make history, and earn bragging rights! Key job responsibilities - Utilize artificial intelligence (includes Generative AI), causal inference, and creative problem-solving skills to improve one of the most significant ecommerce algorithms that impacts millions of shoppers and sellers in the planet. - Partner closely with engineers to put your research and ideas into production on Amazon.com. - Leverage your science expertise to research and deliver novel solutions to explore emerging problem spaces, and create or organize knowledge around them. - Publish papers and file patents to contribute to the machine learning community. - Present ideas to senior leadership (Sr. Managers and above) and mentor Applied Scientists and Engineers with an interest in artificial intelligence. - Provide scientific consultation and influence teams beyond your immediate group, such as, Personalization, Media content teams, and Ads. About the team Buying Experience (BuyX) connects shoppers worldwide with the best product and offer evaluation experiences. Our Homepage guides customers to their next discovery—whether restocking essentials or exploring new Amazon services—through personalized, engaging content. On the Detail Page, we showcase products with tailored experiences across geographies and intents. Our team drives innovation through advanced algorithms, insightful product comparisons, dynamic content policies, and scalable architecture, ensuring every customer makes confident, informed decisions with each visit. We are a team of Scientists, Economists, and Engineers, working together to realize this mission. We operate in a diverse space that includes modeling of customer purchase behavior, advanced simulation and experimentation. We employ a variety of AI/ML, and econometric techniques.

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.

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

We’re seeking a thought leader to direct Advanced ML initiatives aimed at scaling our $600B+ Amazon ecommerce business. This person will also be a deep learning practitioner/thinker and guide the research in these areas. They’ll have the ability to drive cutting edge, product-oriented research and should have a notable publication record. This intellectual thought leader will help enhance the science in addition to developing the thinking of our team. This leader will build / develop the team, direct and shape the science philosophy, and plan / strategize, as we explore domains such as reinforcement learning (RL), optimization, simulation, and leading technology in Large Language Models (LLMs) to facilitate seller recruiting, onboarding, growth, and brand building. Joining this team, you’ll experience the benefits of working in a dynamic, entrepreneurial environment, while leveraging the resources of Amazon [Earth's most customer-centric internet company]. About the team Selling Partner Recruitment and Success (SPRS) builds the programs, tools, systems, and science to recruit new selling partners with valuable selection into Amazon’s stores, drive their engagement with Amazon’s selling programs and services, and empower them to realize their potential for success and sustainable growth in our stores. We use advanced ML techniques to help scale the growth and success of sellers, who contribute over 60% of the sales for Amazon’s e-commerce business. The application of ML in this area is a relatively new focus for our business, and the opportunity is huge!