Careers

Are you passionate about solving complex classification challenges at massive scale? We are seeking a Data Science Manager to join our ASIN Classification team within WAVE (World Wide AI Enablement). In this high-impact role, you will lead a team of scientists and engineers to architect, deploy, and operationalize advanced machine learning models that drive ASIN classification across a range of compliance programs. From supervised and unsupervised ML approaches to Large Language Models and Small Language Models, you will guide your team in harnessing state-of-the-art techniques to deliver accurate, scalable classification solutions for millions of ASINs. Key job responsibilities • Lead and manage a team of Applied Scientists, Data Scientists, and Engineers, fostering a culture of innovation, scientific rigor, and operational excellence • Define the team's science roadmap and prioritize classification initiatives across compliance programs • Own end-to-end delivery of classification solutions from problem framing and data strategy through model deployment and production monitoring • Drive architecture decisions including model selection, feature engineering from product catalogs, and evaluation metric frameworks • Translate ambiguous, large-scale compliance challenges into well-scoped data science and ML workstreams • Collaborate with business teams to convert business requirements into scalable ML solutions • Establish and monitor classification metrics, model performance KPIs, and production health dashboards to ensure continuous improvement • Partner cross-functionally with Science, Engineering, Product, and Operations teams to align science investments with business priorities • Build scalable data environments and ML pipelines to support model training, evaluation, shadow testing, and production inference at scale • Mentor and develop team members through career coaching, technical guidance, and structured growth plans • Communicate complex technical concepts effectively to non-technical stakeholders and senior leadership • Drive operational rigor ensuring zero-disruption deployments, data quality standards, and robust experimentation practices • Stay current with latest research, publications, and application of techniques to production systems

We are seeking a Sr. Applied Scientist to develop cutting-edge machine learning algorithms for motor control systems in robots. In this role, you will focus on creating and optimizing intelligent motor control strategies to enable robots to perform complex, whole-body tasks. Your contributions will be essential in advancing robotics by enabling fluid, reliable, and safe interactions between robots and their environments. Key job responsibilities - Develop controllers that leverage reinforcement learning, imitation learning, or other advanced AI techniques to achieve natural, robust, and adaptive motor behaviors - Collaborate with multi-disciplinary teams to integrate motor control systems with robotic hardware, ensuring alignment with real-world constraints such as actuator dynamics and energy efficiency - Use simulation and real-world testing to refine and validate control algorithms - Stay updated on advancements in robotics, AI, and control systems to apply advanced techniques to robotic motion challenges - Lead technical projects from conception through production deployment - Mentor junior scientists and engineers - Bridge research initiatives with practical engineering implementation About the team Fauna Robotics, an Amazon company, is building capable, safe, and genuinely delightful robots for everyday life. Our goal is simple: make robots people actually want to live and interact with in everyday human spaces. We believe that future won’t arrive until building for robotics becomes far more accessible. Today, too much effort is spent reinventing the fundamentals. We’re changing that by developing tightly integrated hardware and software systems that make it faster, safer, and more intuitive to create real-world robotic products. Our work spans the full stack: mechanical design, control systems, dynamic modeling, and intelligent software. The focus is not just functionality, but experience. We’re building robots that feel responsive, expressive, and genuinely useful. At Fauna, you’ll work at the frontier of this space, helping define how robots move, manipulate, and interact with people in natural environments. It’s an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build. If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you. an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build. If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you.

Application deadline: Jun 15, 2026 The Amazon Robotics Autonomous Mobility software team develops the autonomy software that powers Proteus, Amazon’s first fully autonomous warehouse robot. We are looking for a Senior Applied Scientist to join our perception and localization team. You will be part of an exceptional group of engineers building the platform and architecture for our onboard mapping, perception, motion planning and control software. In addition, you will collaborate with engineers and scientists across the team to develop and enhance our real-time multi-robot simulation capabilities. Key job responsibilities Specific areas of focus may include (but are not limited too): - Researching, designing, and implementing scientific approaches for sensor calibration, including cameras and LIDARs. - Researching, designing, and implementing scientific approaches for SLAM (simultaneous localization and mapping). - Supporting and improving the large-scale deployment of a SLAM system shared across an autonomous robot fleet. - Evaluating and integrating new sensing modalities into an existing autonomy software stack. - Optimizing runtime performance of autonomy algorithms by exploiting underlying hardware acceleration capabilities. - Building frameworks for large-scale replay and analysis of events in pre-recorded sensor data. - Deliver high quality production level code (C++ or Python) and support systems in production. - Collaborate with other functional teams in a robotics organization. - Collaborate with hardware engineering team members on developing systems from prototyping to production level. - Work with stakeholders across hardware and operations teams to iterate on system design and implementation. A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! About the team We are a multi-disciplinary team of collaborative Applied Scientists and Software Engineers with expertise in Computer Vision, SLAM, motion planning and controls. Our mission is to deliver a robust software solution the utilizes state-of-the-art sensor technologies and algorithms to enable safe and efficient operation of autonomous mobile robots throughout the Amazon fulfillment and transportation network. We take this mission seriously and work hard to achieve it, but we have a lot of fun along the way. After all, what's more fun than building robots?

Are you excited to help customers discover the hottest and best reviewed products? The Discovery Tech team helps customers discover and engage with new, popular and relevant products across Amazon worldwide. We do this by combining technology, science, and innovation to build new customer-facing features and experiences alongside advanced tools for marketers. You will be responsible for creating and building critical services that automatically generate, target, and optimize Amazon’s cross-category marketing and merchandising. Through the enablement of intelligent marketing campaigns that leverage machine-learning models, you will help to deliver the best possible shopping experience for Amazon’s customers all over the globe. We are looking for analytical problem solvers who enjoy diving into data, excited about data science and statistics, can multi-task, and can credibly interface between engineering teams and business stakeholders. Your analytical abilities, business understanding, and technical savvy will be used to identify specific and actionable opportunities to solve existing business problems and look around corners for future opportunities. Your domain spans the design, development, testing, and deployment of data-driven and highly scalable machine learning solutions in product recommendation. As an 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. To know more about Amazon science, please visit https://www.amazon.science

Are you ready to build something extraordinary from the ground up? We're looking for a seasoned Applied Science Manager to establish and lead a brand-new team in Bangalore, India, within Alexa Edge AI. This is a rare greenfield opportunity to shape the future of ambient intelligence by pioneering breakthroughs in computer vision, acoustic modeling, and multimodal semantic understanding that will power hundreds of millions of Alexa-enabled devices worldwide. As an Applied Science Manager, you will architect and scale a world-class applied science team that pushes the boundaries of what's possible at the intersection of edge and cloud AI. From enabling seamless Visual ID that recognizes who's in the room, to crafting ultra-low-latency wake word detection that works flawlessly in noisy environments, to building multimodal models that build deep semantic understanding — your work will directly define how Alexa perceives, understands, and interacts with the physical world. You'll operate at the frontier of on-device ML, tackling hard constraints in compute, memory, and power while delivering experiences that feel magical to customers. If you thrive on ambiguity, love building high-performing teams from scratch, and want to ship science that touches millions of lives daily — this is your moment. Key job responsibilities Establish and grow a high-caliber applied science team from the ground up at our new Bangalore site, defining the team's charter, culture, hiring bar, and technical roadmap Recruit, mentor, and develop top-tier scientists and engineers across computer vision, speech/acoustics, and multimodal ML disciplines Foster a culture of scientific rigor, rapid experimentation, customer obsession, and operational excellence Drive R&D of privacy preserving edge solutions like Visual recognition and Acoustic Modeling (Wake Word & Audio Intelligence) optimized for edge deployment on resource-constrained hardware (custom silicon, DSPs, NPUs). Define and execute strategies for optimizing latency, privacy, accuracy, and cost while collaborating with hardware and silicon teams to co-design next-generation AI accelerators and model architectures Own the end-to-end lifecycle from research ideation through experimentation, prototyping, and production deployment at scale Establish robust benchmarking, A/B testing, and metrics frameworks to measure real-world impact Partner closely with engineering, product, and UX teams to translate scientific breakthroughs into delightful customer experiences Shape the long-term science and technology roadmap for Alexa's perceptual AI capabilities Represent the team in org-wide science reviews, patent filings, and publications at top-tier venues (NeurIPS, ICML, CVPR, ICASSP, etc.) Build strong cross-site collaboration with teams in Sunnyvale, Boston and other global locations A day in the life As an Applied Science Manager in Alexa Edge AI, you'll split your time between deep technical engagement and people leadership — reviewing experiment results, debating model architectures with your scientists, guiding on trade-offs, and connecting with cross-site partners to align on roadmap priorities and influence org-wide direction. Initially, a significant portion of your energy goes toward building the team itself: interviewing exceptional candidates, calibrating the hiring bar, coaching scientists on career growth, and shaping the culture of a brand-new site. You stay hands-on with the research landscape, refine your science roadmap, and ensure your team has clear priorities — all while context-switching fluidly between being a technical thought leader, a strategic voice in leadership forums, and a mentor to your growing team. No two days are the same — but every day, you're building a team, pushing science forward, and shipping intelligence to the edge. About the team The Alexa Edge AI team has a mission to deliver best in class, resource efficient multimodal AI models in support of various perception (vision, audio and speech) based applications for Echo Family of Devices within Amazon.

Do you ever struggle to explain your work? How's this: "Do you shop at Amazon? Do you know that box that says 'Add to Cart' and shows a price? Our team owns the model which picks that offer and the customer experience around the display of the offer price and the elements surrounding the 'Add to Cart' button which inform a purchase decision. We pick and display offers several billion times a day across all surfaces (mobile app, mobile web, desktop, Alexa shopping) worldwide. Our mission is to be the world’s first and most trusted choice for every customer on earth to discover and evaluate any product or service. Our team blends machine learning models to rank and select the best offer from the most trusted merchant for all products sold on Amazon along with a world-class front-end user experience for offer comparison to our global customers. We are responsible for the experiences and services that enable developers, including our own, to create tailored shopping experiences for every customer, product, business and marketplace offered by Amazon. We build scalable and extensible frameworks which allow for many teams at Amazon to innovate within the Offers Experience in a federated manner. If you are passionate about influencing and delivering the next-generation Amazon customer buying experience, we want to meet you. We are looking for a Senior Economist to join one of the most impactful and visible teams in Amazon. In this role you will work with business stakeholders throughout Amazon and provide technical direction and business expertise to strategize and help launch new businesses and features for our customers. You will use data to justify customer friendly decisions and present customer and financial impact of the changes we make to our stakeholders. You will work closely with other economists, engineers, product managers, applied scientists, TPMs, managers, and senior leadership team to understand and drive business impact. Successful candidates will have experience working on multiple projects with different stakeholders, make data driven decisions, have strong communication skills to interact with executives, non-technical and technical individuals and have a high technical bar along with a passion for people and project management. This is an opportunity to work with a team that drives one of the most coveted real estate in the E-commerce, the Amazon ‘Buy Box’ on Amazon Product Detail Page, Amazon Search Page , multiple buying widgets etc. on the Amazon desktop, mobile and tablet environments.

Are you excited about leveraging and extending state-of-the-art Deep Learning, Information Retrieval, Natural Language Processing, Computer Vision algorithms to solve customer problems at the scale of Amazon? As an Applied Scientist Intern, you will be working in the Melbourne office in a fast-paced, cross-disciplinary team of experienced R&D scientists. You will take on complex problems, work on solutions that leverage existing academic and industrial research, and utilize your own out-of-the-box pragmatic thinking. In addition to coming up with novel solutions and prototypes, you may even deliver these to production in customer facing products. Key job responsibilities - Develop novel solutions and build prototypes - Work on complex problems in Deep Learning and Generative AI - Contribute to research that could significantly impact Amazon operations - Collaborate with a diverse team of experts in a fast-paced environment - Present your research findings to both technical and non-technical audiences - Collaborate with scientists on writing and submitting papers to top ML conferences, e.g. NeurIPS, ICML, ICLR, AISTATS, ACL ICCV, CVPR, KDD. Key Opportunities: - Work in a team of ML scientists to solve applied science problems at the scale of Amazon - Access to Amazon services and hardware - Potentially deliver solutions to production in customer-facing applications - Opportunities to be hired full-time after the internship Join us in shaping the future of AI at Amazon. Apply now and turn your research into real-world solutions!

Amazon’s Last Mile Team is looking for a passionate individual with strong optimization and analytical skills to join its Last Mile Science team in the endeavor of designing and improving the most complex planning of delivery network in the world. Last Mile builds global solutions that enable Amazon to attract an elastic supply of drivers, companies, and assets needed to deliver Amazon's and other shippers' volumes at the lowest cost and with the best customer delivery experience. Last Mile Science team owns the core decision models in the space of jurisdiction planning, delivery channel and modes network design, capacity planning for on the road and at delivery stations, routing inputs estimation and optimization. Our research has direct impact on customer experience, driver and station associate experience, Delivery Service Partner (DSP)’s success and the sustainable growth of Amazon. Optimizing the last mile delivery requires deep understanding of transportation, supply chain management, pricing strategies and forecasting. Only through innovative and strategic thinking, we will make the right capital investments in technology, assets and infrastructures that allows for long-term success. Our team members have an opportunity to be on the forefront of supply chain thought leadership by working on some of the most difficult problems in the industry with some of the best product managers, scientists, and software engineers in the industry. Key job responsibilities Candidates will be responsible for developing solutions to better manage and optimize delivery capacity in the last mile network. The successful candidate should have solid research experience in one or more technical areas of Operations Research or Machine Learning. These positions will focus on identifying and analyzing opportunities to improve existing algorithms and also on optimizing the system policies across the management of external delivery service providers and internal planning strategies. They require superior logical thinkers who are able to quickly approach large ambiguous problems, turn high-level business requirements into mathematical models, identify the right solution approach, and contribute to the software development for production systems. To support their proposals, candidates should be able to independently mine and analyze data, and be able to use any necessary programming and statistical analysis software to do so. Successful candidates must thrive in fast-paced environments, which encourage collaborative and creative problem solving, be able to measure and estimate risks, constructively critique peer research, and align research focuses with the Amazon's strategic needs.

Our team is at the forefront of machine learning research. Led by scientists including Dean Foster, the team is dedicated to developing innovative RL algorithms and applying them to complex, real-world challenges in Amazon's global inventory and supply chain network. Our focus is not just on advancing theoretical knowledge but also on implementing these insights to optimize operations and enhance customer satisfaction. We foster a collaborative environment where exploration of new ideas and tackling complex problems is encouraged. The supply chain spans a wide range of operations,managing decisions that impact billions of dollars worth of inventory. For scientists passionate about impactful research in machine learning and AI, our team offers a dynamic and fulfilling environment to make a tangible difference in the field and Amazon's operations. Key job responsibilities - Design, implement, and evaluate innovative models, agents, and software prototypes. - Collaborate with a team of experienced scientists to drive technological advancements. - Develop innovative solutions to complex business problems in collaboration with partner teams. - Contribute to Amazon's global science community through collaboration and publication of ground-breaking research. - Engage in research projects that contribute to the wider scientific community, sharing findings through publications in top-tier journals and conferences. A day in the life A day in the life As a part of our team, you will be working alongside thought leaders like Dean Foster, contributing to academic research and complex, real-world applications. Your work will directly influence Amazon's global inventory planning systems, shaping decisions that affect billions of dollars worth of inventory and a wide array of product lines. You will tackle complex inventory planning challenges using Reinforcement Learning, contributing both to the theoretical aspect of the field and its practical applications. We value innovative thinking and the ability to approach problems from new perspectives. Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: - Medical, Dental, and Vision Coverage - Maternity and Parental Leave Options - Paid Time Off (PTO) - 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!

Come join the AWS Agentic AI science team in building the next generation models for intelligent automation. AWS, the world-leading provider of cloud services, has fostered the creation and growth of countless new businesses, and is a positive force for good. Our customers bring problems that will give Applied Scientists like you endless opportunities to see your research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and workshops. We are looking for world class researchers with experience in one or more of the following areas - autonomous agents, API orchestration, Planning, large multimodal models (especially vision-language models), reinforcement learning (RL) and sequential decision making.