Careers

We are seeking a talented, customer-focused applied scientist to join our JCI Measurement and Optimization Science Team (JCI MOST), with a charter to build scalable systems that automatically detect pricing defects, implement intelligent corrections, measure intervention impacts, and deliver data-driven pricing strategies to leadership. This role requires an individual with exceptional machine learning, LLM, and Causal Inference expertise, strong system architecture capabilities, excellent cross-functional collaboration skills, business acumen, and an entrepreneurial spirit to drive measurable improvements in pricing quality and competitiveness. We are looking for an experienced innovator who is a self-starter, comfortable with ambiguity, demonstrates strong attention to detail, and thrives in a fast-paced, data-driven environment. Key job responsibilities Key Job Responsibilities • Build scalable defect detection systems that automatically identify pricing anomalies, competitive gaps, and quality issues across millions of products using ML and LLM models and real-time monitoring • Deploy automated defect remediation with intelligent pricing recommendations, and validation frameworks that reduce manual intervention requirements • Measure impact and drive strategy by establishing robust measurement frameworks, designing large-scale experiments, building attribution models, and developing executive dashboards that translate findings into actionable insights for leadership • Lead cross-functional collaboration by partnering with product, engineering, and science teams to deploy solutions at scale while communicating complex technical concepts clearly to executive audiences • Stay at the forefront of innovation by applying state-of-the-art techniques in ML, deep learning, LLM, and causal inference to pricing quality challenges while fostering rapid experimentation and continuous learning

RBS (Retail Business Services) Tech team works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects at scale. Our platforms help in improving the CX in all phases of customer journey, including selection, discoverability & fulfilment, buying experience and post-buying experience (product quality and customer returns). As a Sciences team in RBS Tech, we focus on foundational ML research and develop scalable state-of-the-art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to multi-modal understanding (text and visual), supervised and unsupervised techniques, multi-task learning, multi-label classification, aspect and topic extraction for Customer Anecdote Mining, product similarity, using GenAI, LLMs, NLP and Computer Vision. Key job responsibilities As an Applied Science Manager, you will be responsible to design and deploy scalable GenAI, NLP and Computer Vision solutions that will impact the content visible to millions of customer and solve key customer experience issues. You will Lead scientists on the team and oversee research and development projects at various stages ranging from initial exploration to deployment into production systems. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will help the team leverage your expertise, by coaching and mentoring. You will contribute to the professional development of colleagues, improving their technical knowledge and the engineering practices. You will create the environment in the team to file for patents and/or publish research work where opportunities arise. You will impact the large product strategy, identifies new business opportunities and provides strategic direction to the team.

Amazon Industrial Robotics is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models. We leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence. We are pioneering the development of robotics foundation models that: - Enable unprecedented generalization across diverse tasks - Integrate multi-modal learning capabilities (visual, tactile, linguistic) - Accelerate skill acquisition through demonstration learning - Enhance robotic perception and environmental understanding - Streamline development processes through reusable capabilities The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment. Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration. As an Applied Scientist, you will develop and improve machine learning systems that help robots perceive, reason, and act in real-world environments. You will leverage state-of-the-art models (open source and internal research), evaluate them on representative tasks, and adapt/optimize them to meet robustness, safety, and performance needs. You will invent new algorithms where gaps exist. You’ll collaborate closely with research, controls, hardware, and product-facing teams, and your outputs will be used by downstream teams to further customize and deploy on specific robot embodiments. Key job responsibilities - Leverage state-of-the-art models for targeted tasks, environments, and robot embodiments through fine-tuning and optimization. - Execute rapid, rigorous experimentation with reproducible results and solid engineering practices, closing the gap between sim and real environments. - Build and run capability evaluations/benchmarks to clearly profile performance, generalization, and failure modes. - Contribute to the data and training workflow: collection/curation, dataset quality/provenance, and repeatable training recipes. - Write clean, maintainable, well commented and documented code, contribute to training infrastructure, create tools for model evaluation and testing, and implement necessary APIs - Stay current with latest developments in foundation models and robotics, assist in literature reviews and research documentation, prepare technical reports and presentations, and contribute to research discussions and brainstorming sessions. - Work closely with senior scientists, engineers, and leaders across multiple teams, participate in knowledge sharing, support integration efforts with robotics hardware teams, and help document best practices and methodologies.

Amazon’s The Middle Mile Science group is looking for a Senior Applied Scientist specializing in design and evaluation of algorithms for predictive modeling and optimization applied to large-scale transportation planning systems. This includes the development of novel machine learning and artificial intelligence techniques to improve on marketplace optimization solutions. The Middle Mile Science group is charged with developing an evolving suite of optimization tools to facilitate the design of efficient air and ground transport networks, optimize the flow of packages within the network to efficiently align network capacity and shipment demand, set prices, and effectively utilize scarce resources, such as aircraft and trucks. The scale of Amazon’s fulfillment operations challenges us to design, build and operate robust transportation networks that minimize the overall operational cost while meeting all customer deadlines. Real-time execution of our network depends on state-of-the-art artificial intelligence tools to coordinate the actions of thousands of operators and drivers in real time. Amazon often finds existing techniques do not effectively match our unique business needs, which necessitates the innovation and development of new approaches and algorithms to find an adequate solution. As a Sr. Applied Scientist responsible for middle mile transportation, you will be working closely with different teams including business leaders and engineers to design and build scalable products operating across multiple transportation modes. You will create experiments and prototype implementations of new learning algorithms and prediction techniques. You will have exposure to top level leadership to present findings of your research. You will also work closely with other scientists and engineers to implement your models within our production system. You will implement solutions that are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility, and make decisions that affect the way we build and integrate algorithms across our product portfolio. About the team Our Middle Mile Marketplace Science team builds the algorithms for Amazon’s rapidly growing freight marketplace. Amazon contracts with 3P shippers and a network of independent carriers, using a mix of contract structures with varying service and risk profiles. Our work focuses on mechanisms and learning algorithms to optimize pricing and matching in this complex marketplace, and continually improve the experience for carriers and shippers. This is an area with many challenging problems and a huge business impact for Amazon!

At Amazon Selection and Catalog Systems (ASCS), our mission is to power the online buying experience for customers worldwide so they can find, discover, and buy any product they want. We innovate on behalf of our customers to ensure uniqueness and consistency of product identity and to infer relationships between products in Amazon Catalog to drive the selection gateway for the search and browse experiences on the website. We're solving a fundamental AI challenge: establishing product identity and relationships at unprecedented scale. Using Generative AI, Visual Language Models (VLMs), and multimodal reasoning, we determine what makes each product unique and how products relate to one another across Amazon's catalog. The scale is staggering: billions of products, petabytes of multimodal data, millions of sellers, dozens of languages, and infinite product diversity—from electronics to groceries to digital content. The research challenges are immense. GenAI and VLMs hold transformative promise for catalog understanding, but we operate where traditional methods fail: ambiguous problem spaces, incomplete and noisy data, inherent uncertainty, reasoning across both images and textual data, and explaining decisions at scale. Establishing product identities and groupings requires sophisticated models that reason across text, images, and structured data—while maintaining accuracy and trust for high-stakes business decisions affecting millions of customers daily. Amazon's Item and Relationship Platform group is looking for an innovative and customer-focused applied scientist to help us make the world's best product catalog even better. In this role, you will partner with technology and business leaders to build new state-of-the-art algorithms, models, and services to infer product-to-product relationships that matter to our customers. You will pioneer advanced GenAI solutions that power next-generation agentic shopping experiences, working in a collaborative environment where you can experiment with massive data from the world's largest product catalog, tackle problems at the frontier of AI research, rapidly implement and deploy your algorithmic ideas at scale, across millions of customers. Key job responsibilities * Formulate novel research problems at the intersection of GenAI, multimodal learning, and large-scale information retrieval—translating ambiguous business challenges into tractable scientific frameworks * Design and implement leading models leveraging VLMs, foundation models, and agentic architectures to solve product identity, relationship inference, and catalog understanding at billion-product scale * Pioneer explainable AI methodologies that balance model performance with scalability requirements for production systems impacting millions of daily customer decisions * Own end-to-end ML pipelines from research ideation to production deployment—processing petabytes of multimodal data with rigorous evaluation frameworks * Define research roadmaps aligned with business priorities, balancing foundational research with incremental product improvements * Mentor peer scientists and engineers on advanced ML techniques, experimental design, and scientific rigor—building organizational capability in GenAI and multimodal AI * Represent the team in the broader science community—publishing findings, delivering tech talks, and staying at the forefront of GenAI, VLM, and agentic system research

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 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 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. - 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. Basic qualifications: - 3+ years experience building ML models for business application. - PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience. - Experience programming in Python, Java, C++ or related languages. - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing. Preferred qualifications: - Experience using Unix/Linux. - Experience in professional software development. - Experience in patents or publications at top-tier peer-reviewed conferences or journals. - Master's degree or above in computer science, computer engineering, or related field.

Amazon has launched a new research lab in San Francisco to develop foundational capabilities for useful AI agents. We’re enabling practical AI to make our customers more productive, empowered, and fulfilled. In particular, our work combines large language models (LLMs) with reinforcement learning (RL) to solve reasoning, planning, and world modeling in both virtual and physical environments. Our research builds on that of Amazon’s broader AGI organization, which recently introduced Amazon Nova, a new generation of state-of-the-art foundation models (FMs). Our lab is a small, talent-dense team with the resources and scale of Amazon. Each team in the lab has the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research. We’re entering an exciting new era where agents can redefine what AI makes possible. We’d love for you to join our lab and build it from the ground up! Key job responsibilities You will be responsible for maintaining our task management system which supports many internal and external stakeholders and ensures we are able to continue adding orders of magnitude more data and reliability.

Are you passionate about transforming how Amazon identifies and remediates security risks at scale? Does the prospect of using data science and AI to protect Amazon's most critical business operations excite you? Stores BST Risk Engineering builds data-driven risk intelligence solutions that help security teams across Amazon's stores identify, prioritize, and remediate strategic security risks. Our customers range from security engineers managing thousands of vulnerabilities to business leaders making strategic risk decisions. We use machine learning, generative AI, and large-scale data analysis to solve diverse security risks at a very large scale. Your responsibilities will include developing machine learning models for automated fraud detection and pattern recognition, building clustering algorithms that identify root causes across thousands of security issues, and creating data correlation pipelines that integrate security signals from multiple sources. You'll use advanced AI and Data Science techniques for fraud detection, unsupervised learning for pattern discovery, and generative AI for automated analysis at scale. Your work will directly enable security teams to shift from manual analysis taking weeks to automated insights delivered in minutes. We're looking for data scientists who can prototype and productionize innovative models using supervised, unsupervised, and reinforcement learning techniques. You'll work on problems like correlating external threat intelligence with asset inventories, building statistical profiles to detect evolving fraud patterns, and designing confidence scoring systems for real-time risk categorization. If you want to apply machine learning to never-before-solved security problems at Amazon scale, this is your team. Key job responsibilities - Demonstrate thorough technical knowledge on feature engineering of massive datasets, effective exploratory data analysis, and model building using industry standard AI/ML models and working with Large Language Models - With your broad expertise in a variety of data science disciplines, recommend the right data science strategy and drive solution to complex or ambiguous problems - Work closely with internal stakeholders like the business teams, engineering teams and partner teams, influence their strategies to align with your focus area - Innovate by adapting new modeling techniques and procedures - Passionate about working with huge data sets ( training/fine tuning) and be someone who loves to bring datasets together to answer business questions. You should have deep expertise in creation and management of datasets - Exposure at implementing and operating stable, scalable data flow solutions from production systems into end-user facing applications/reports. These solutions will be fault tolerant, self-healing and adaptive. - Show good judgment when making trade-offs between short-term customer, market, or research needs and long-term operations or technology needs. About the team About Amazon Security Diverse Experiences Amazon Security 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 Amazon Security? At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & 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, training, 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.

Join us at the Amazon's sustainability initiatives to work on environmental and social advancements to support Amazon's long term worldwide sustainability strategy. At Amazon, we're working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people. The Worldwide Sustainability (WWS) organization capitalizes on Amazon’s scale and speed to build a more resilient and sustainable company. We manage our social and environmental impacts globally, and drive solutions that enable our customers, businesses, and the world to become more sustainable. Sustainability Science and Innovation (SSI) is a multi-disciplinary team within WW Sustainability combining science, analytics, economics, statistics, machine learning, product development, and engineering expertise. We use data across the sustainability imperatives (carbon, water, waste, biodiversity, environmental risk and more) and these skills and capabilities to identify, develop, experiment, and scale the scientific solutions and innovations necessary for Amazon, customers and partners to help them solve their hardest unmet and evolving sustainability needs and goals. The Sustainability Science and Innovation team is looking for a Sr. Applied Scientist to collaborate closely with Economists and Environmental Scientists to build the AI/ML foundation of the future. You will define strategy and implement tooling to identify, ingest, harmonize, store, and maintain strategic models and data from both internal and external sources. These models and datasets must cover a wide range of topics in emerging areas and applications of AI for sustainability. This AI solutions development will support Amazon-wide sustainability initiatives like carbon footprint, climate risk monitoring, and social responsibility through the supply chain. These datasets must cover a wide range of topics such as geographic regions and data formats to unlock foundational AI research in emerging areas and applications. These solutions development will support Amazon-wide sustainability initiatives like carbon footprinting, climate risk monitoring, and social responsibility through the supply chain. If you see yourself as a hands-on leader and innovator at the intersection of AI, data, and sustainability, we'd like to connect with you. You don't necessarily have to be an expert in sustainability and climate domains. Key job responsibilities - Designing, implementing, and maintaining data and AI/ML infrastructure to support a wide variety of large and complex data sets, ensuring high performance, availability, and integrity. - Identifying and solving data needs for Gen AI and foundational model training and benchmarking for tasks across the sustainability domain. - Developing and optimizing robust data pipelines for internal data from sources such as Product Lifecycle Management tools, Product Details (images, text, and structured data), Inventory Management Platforms, and financial systems. - Design and implement web-scale data collection for images, text, structured data across locations and sustainability domains. - Develop comprehensive monitoring, alarming, and data quality controls for all of the above. - Partnering with Scientists and Software Engineers to create our data collection strategy and ML Ops best practices. About the team Diverse Experiences: World Wide Sustainability 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. Inclusive Team Culture: 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 (inclusive 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

At Amazon Robotics, we design advanced robotic systems capable of intelligent perception, learning, and action alongside humans, all on a large scale. Our goal is to develop robots that increase productivity and efficiency at the Amazon fulfillment centers while ensuring the safety of workers. We are seeking an Applied Scientist to develop innovative, scalable solutions in feedback control and state estimation for robotic systems, with a focus on contact-rich manipulation tasks. In this role, you will formulate physics-based models of robotic systems, perform analytical and numerical studies, and design control and estimation algorithms that integrate fundamental principles with data-driven techniques. You will collaborate with a world-class team of experts in perception, machine learning, motion planning, and feedback controls to innovate and develop solutions for complex real-world problems. As part of your work, you will investigate applicable academic and industry research to develop, implement, and test solutions that support product features. You will also design and validate production designs. To succeed in this role, you should demonstrate a strong working knowledge of physical systems, a desire to learn from new challenges, and the problem-solving and communication skills to work within a highly interactive and experienced team. Candidates must show a hands-on passion for their work and the ability to communicate their ideas and concepts both verbally and visually. Key job responsibilities - Research, design, implement, and evaluate feedback control, estimation, and motion-planning algorithms, ensuring effective integration with perception, manipulation, and system-level components. - Develop experiments, simulations, and hardware prototypes to validate control algorithms, and optimization techniques in contact-rich manipulation and other challenging scenarios. - Collaborate with software engineering teams to enable scalable, real-time, and maintainable implementations of algorithms in production systems. - Partner with cross-functional teams across hardware, systems engineering, science, and operations to transition algorithms from early prototyping to robust, production-ready solutions. - Engage with stakeholders at all levels to iterate on system design, define requirements, and drive integration of control and estimation capabilities into Amazon Robotics platforms. 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!