Careers

Amazon Industrial Robotics Group 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 an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic dexterous 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. At Amazon Industrial Robotics Group, we leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at an 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 dexterous manipulation system that: - Enables unprecedented generalization across diverse tasks - Enables contact-rich manipulation in different environments - Seamlessly integrates low-level skills and high-level behaviors - Leverage mechanical intelligence, multi-modal sensor feedback and advanced control techniques. 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. Key job responsibilities - Design and implement methods for dexterous manipulation - Design and implement methods for use of dexterous end effectors with force and tactile sensing - Develop a hierarchical system that combines low-level control with high-level planning - Utilize state-of-the-art manipulation models and optimal control techniques

Amazon B2B Payments and Lending (ABPL) revolutionize financial services for businesses of all sizes, anywhere in the world, enabling them to delight their customers and make a positive impact to the communities they serve. We never stop innovating to earn their trust by leveraging our scale, insights, and technology, and raising the bar with simple, secure, and seamless solutions. ABPL organization is seeking a highly quantitative, experienced Data Scientist to drive the development of science analytics and insights capabilities. You will succeed in this role if you are an organized self-starter who can learn new technologies quickly and excel in a fast-paced environment. In this position, you will be a key contributor and sparring partner, developing analytics and insights that global executive management teams and business leaders will use to define global strategies and deep dive businesses. Our team is an Analytics team, offering a unique opportunity to build a new set of analytical experiences from the ground up. You will be part the team that is focused on developing analytical solutions for our customers/Merchants (Product/Marketing/Finance/Operations team). The position is based in India but will interact with global leaders and teams in Europe, Japan, US, and other regions. You should be highly analytical, resourceful, customer focused, team-oriented, and have an ability to work independently. You will be comfortable thinking big and diving deep. A proven track record in taking on end-to-end ownership and successfully delivering results in a fast-paced, dynamic business environment is strongly preferred. Key job responsibilities • Partner with technical and non-technical stakeholders across every step of the science project lifecycle to deliver impactful solutions • Design and deploy AI-powered analytical services that deliver automated, actionable insights through predictive and prescriptive ML solutions, enabling business teams to make data-driven decisions and accelerate growth. • Design, develop, implement, and test forecasting solutions for planning and goal-setting exercises across various payment products and programs within the ABPL organization. • Develop and implement agentic AI frameworks to streamline repetitive business operations and create intelligent, customer-facing solutions that enhance user experience and operational efficiency • Design and implement marketing analytics solutions including impact measurement, attribution modeling, and personalization models to optimize marketing effectiveness and ROI • Develop and implement real-time anomaly detection mechanisms and early-warning systems to proactively identify business risks and opportunities • Partner with product, tech teams, BIE/DE to build robust and scalable science solutions integrated with in-house reporting and BI tools using SQL, Python, and Spark • Lead training and informational sessions to educate stakeholders on science capabilities and methodologies • Create, share, and present comprehensive documents summarizing findings and recommendations to all levels of the organization • Drive thought leadership in data science by staying at the forefront of emerging research, identifying breakthrough methodologies, and shaping the team's long-term technical roadmap through innovative problem-solving approaches. • Communicate effectively with cross-functional teams including product, business, technology, and other science teams About the team

Are you passionate to join an innovative team of scientists and engineers who use machine learning and AI techniques to create state-of-the-art solutions to help seller succeed on Amazon? The Selling Partner Growth org is looking for a Senior Applied Scientist to lead us on our mission to understand demand side signals on Amazon, and empower sellers to grow their business and provide a great customer experience. As a Senior Applied Scientist on our team of scientists and engineers, you will have opportunities to create significant impact on our systems, our business and most importantly, our customers as we take on challenges that can revolutionize the e-commerce industry. You will identify specific and actionable opportunities to solve business problems, propose state-of-the-art solutions and collaborate with engineering, and business teams for future innovation. You need to be a great translation between ambiguous business domains and rigorous scientific solutions, an expert at inventing and simplify, and a good communicator to surface insights and recommendations to audiences of varying levels of technical sophistication. Major responsibilities - Use machine learning and AI techniques to create scalable seller-facing solutions - Analyze and extract relevant information from large amounts of Amazon's historical business data to help automate and optimize key processes - Design, development and evaluation of highly innovative models - Work closely with software engineering teams to drive real-time model implementations and new feature creations To know more about Amazon science, Please visit https://www.amazon.science

Lead ML teams building large-scale forecasting and optimization systems that power Amazon’s global transportation network and directly impact customer experience and cost. As an Applied Science Manager, you will set scientific direction, mentor applied scientists, and partner with engineering and product leaders to deliver production-grade ML solutions at massive scale. Key job responsibilities 1. Lead and grow a high-performing team of Applied Scientists, providing technical guidance, mentorship, and career development. 2. Define and own the scientific vision and roadmap for ML solutions powering large-scale transportation planning and execution. 3. Guide model and system design across a range of techniques, including tree-based models, deep learning (LSTMs, transformers), LLMs, and reinforcement learning. 4. Ensure models are production-ready, scalable, and robust through close partnership with stakeholders. Partner with Product, Operations, and Engineering leaders to enable proactive decision-making and corrective actions. 5. Own end-to-end business metrics, directly influencing customer experience, cost optimization, and network reliability. 6. Help contribute to the broader ML community through publications, conference submissions, and internal knowledge sharing. A day in the life Your day includes reviewing model performance and business metrics, guiding technical design and experimentation, mentoring scientists, and driving roadmap execution. You’ll balance near-term delivery with long-term innovation while ensuring solutions are robust, interpretable, and scalable. Ultimately, your work helps improve delivery reliability, reduce costs, and enhance the customer experience at massive scale.

This is currently a 12 month temporary contract opportunity with the possibility to extend to 24 months based on business needs. The Artificial General Intelligence (AGI) team is seeking a dedicated, skilled, and innovative Applied Scientist with a robust background in machine learning, statistics, quality assurance, auditing methodologies, and automated evaluation systems to ensure the highest standards of data quality, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As part of the AGI team, an Applied Scientist will collaborate closely with core scientist team developing Amazon Nova models. They will lead the development of comprehensive quality strategies and auditing frameworks that safeguard the integrity of data collection workflows. This includes designing auditing strategies with detailed SOPs, quality metrics, and sampling methodologies that help Nova improve performances on benchmarks. The Applied Scientist will perform expert-level manual audits, conduct meta-audits to evaluate auditor performance, and provide targeted coaching to uplift overall quality capabilities. A critical aspect of this role involves developing and maintaining LLM-as-a-Judge systems, including designing judge architectures, creating evaluation rubrics, and building machine learning models for automated quality assessment. The Applied Scientist will also set up the configuration of data collection workflows and communicate quality feedback to stakeholders. An Applied Scientist will also have a direct impact on enhancing customer experiences through high-quality training and evaluation data that powers state-of-the-art LLM products and services. A day in the life An Applied Scientist with the AGI team will support quality solution design, conduct root cause analysis on data quality issues, research new auditing methodologies, and find innovative ways of optimizing data quality while setting examples for the team on quality assurance best practices and standards. Besides theoretical analysis and quality framework development, an Applied Scientist will also work closely with talented engineers, domain experts, and vendor teams to put quality strategies and automated judging systems into practice.

This is currently a 12 month temporary contract opportunity with the possibility to extend to 24 months based on business needs. The Artificial General Intelligence (AGI) team is seeking a dedicated, skilled, and innovative Applied Scientist with a robust background in machine learning, statistics, quality assurance, auditing methodologies, and automated evaluation systems to ensure the highest standards of data quality, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As part of the AGI team, an Applied Scientist will collaborate closely with core scientist team developing Amazon Nova models. They will lead the development of comprehensive quality strategies and auditing frameworks that safeguard the integrity of data collection workflows. This includes designing auditing strategies with detailed SOPs, quality metrics, and sampling methodologies that help Nova improve performances on benchmarks. The Applied Scientist will perform expert-level manual audits, conduct meta-audits to evaluate auditor performance, and provide targeted coaching to uplift overall quality capabilities. A critical aspect of this role involves developing and maintaining LLM-as-a-Judge systems, including designing judge architectures, creating evaluation rubrics, and building machine learning models for automated quality assessment. The Applied Scientist will also set up the configuration of data collection workflows and communicate quality feedback to stakeholders. An Applied Scientist will also have a direct impact on enhancing customer experiences through high-quality training and evaluation data that powers state-of-the-art LLM products and services. A day in the life An Applied Scientist with the AGI team will support quality solution design, conduct root cause analysis on data quality issues, research new auditing methodologies, and find innovative ways of optimizing data quality while setting examples for the team on quality assurance best practices and standards. Besides theoretical analysis and quality framework development, an Applied Scientist will also work closely with talented engineers, domain experts, and vendor teams to put quality strategies and automated judging systems into practice.

This is currently a 12 month temporary contract opportunity with the possibility to extend to 24 months based on business needs. The Artificial General Intelligence (AGI) team is seeking a dedicated, skilled, and innovative Applied Scientist with a robust background in machine learning, statistics, quality assurance, auditing methodologies, and automated evaluation systems to ensure the highest standards of data quality, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As part of the AGI team, an Applied Scientist will collaborate closely with core scientist team developing Amazon Nova models. They will lead the development of comprehensive quality strategies and auditing frameworks that safeguard the integrity of data collection workflows. This includes designing auditing strategies with detailed SOPs, quality metrics, and sampling methodologies that help Nova improve performances on benchmarks. The Applied Scientist will perform expert-level manual audits, conduct meta-audits to evaluate auditor performance, and provide targeted coaching to uplift overall quality capabilities. A critical aspect of this role involves developing and maintaining LLM-as-a-Judge systems, including designing judge architectures, creating evaluation rubrics, and building machine learning models for automated quality assessment. The Applied Scientist will also set up the configuration of data collection workflows and communicate quality feedback to stakeholders. An Applied Scientist will also have a direct impact on enhancing customer experiences through high-quality training and evaluation data that powers state-of-the-art LLM products and services. A day in the life An Applied Scientist with the AGI team will support quality solution design, conduct root cause analysis on data quality issues, research new auditing methodologies, and find innovative ways of optimizing data quality while setting examples for the team on quality assurance best practices and standards. Besides theoretical analysis and quality framework development, an Applied Scientist will also work closely with talented engineers, domain experts, and vendor teams to put quality strategies and automated judging systems into practice.

As part of the AWS Solutions organization, we have a vision to provide business applications, leveraging Amazon’s unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers’ businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon’s real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use. The Team Just Walk Out (JWO) is a new kind of store with no lines and no checkout—you just grab and go! Customers simply use the Amazon Go app to enter the store, take what they want from our selection of fresh, delicious meals and grocery essentials, and go! Our checkout-free shopping experience is made possible by our Just Walk Out Technology, which automatically detects when products are taken from or returned to the shelves and keeps track of them in a virtual cart. When you’re done shopping, you can just leave the store. Shortly after, we’ll charge your account and send you a receipt. Check it out at amazon.com/go. Designed and custom-built by Amazonians, our Just Walk Out Technology uses a variety of technologies including computer vision, sensor fusion, and advanced machine learning. Innovation is part of our DNA! Our goal is to be Earths’ most customer centric company and we are just getting started. We need people who want to join an ambitious program that continues to push the state of the art in computer vision, machine learning, distributed systems and hardware design. Key job responsibilities Everyone on the team needs to be entrepreneurial, wear many hats and work in a highly collaborative environment that’s more startup than big company. We’ll need to tackle problems that span a variety of domains: computer vision, image recognition, machine learning, real-time and distributed systems. As a Sr. Applied Scientist, you will help solve a variety of technical challenges and mentor other scientists. You will be the thought leader of the team. You will tackle challenging, novel situations every day and given the size of this initiative, you’ll have the opportunity to work with multiple technical teams at Amazon in different locations. You should be comfortable with a degree of ambiguity that’s higher than most projects and relish the idea of solving problems that, frankly, haven’t been solved at scale before - anywhere. Along the way, we guarantee that you’ll learn a ton, have fun and make a positive impact on millions of people. Key job responsibilities - Develop a novel framework and advance the theory and practice of multi-object tracking, re-identification, person activity understanding, multi-modal foundation model, and generic video understanding - Create innovative techniques for efficient visual processing that can scale to real-world applications - Investigate approaches to reduce the computational and data requirements of visual AI systems About the team AWS Solutions As part of the AWS solutions organization, we have a vision to provide business applications, leveraging Amazon's unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers' businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. we blend vision with curiosity and Amazon's real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use. About AWS Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

We are seeking an exceptional Senior Data Scientist to join our JP Seller Services team, where you will play a pivotal role in enabling seller growth and success on Amazon Marketplace through innovative products, technology, and data-driven solutions. As a key member of JP Seller Services, you will collaborate with cross-functional stakeholders across Amazon to develop sophisticated AI-native recommendation systems and problem-solving products through advanced analytics, machine learning, and generative AI. These solutions will enable seller business growth on Amazon Marketplace and serve as key strategic pillars that influence our entire seller base. The ideal candidate combines deep technical knowledge in generative AI, machine learning, and statistical modeling with strategic thinking to address complex business challenges through scalable solutions. Key job responsibilities (1) Build and scale end-to-end AI-native recommendation models using generative AI/ML to unlock business growth opportunities. (2) Create scalable, data-driven mechanisms to identify critical and urgent seller challenges through scientific modeling. (3) Collaborate with stakeholders to transform business insights into rigorous scientific solutions.

Join our Generative AI focus team to innovate Software Development at Amazon Are you ready to be part of a team that's redefining the future of software engineering? We are seeking an Applied Scientist to lead research in agentic AI systems for developer tooling at Amazon. You will join a small, focused cross functional team investigating how autonomous agents can reliably perform complex tasks on behalf of software engineers. 🎯 Our Mission We’re building the next generation of development tools, uncovering how LLMs can originate new ways of thinking, building, and collaborating. 💫 What Makes Us Different * Ground-floor opportunity to shape the future of software development * Direct impact on Amazon's global engineering practices * Culture of experimentation and innovative thinking 🔍 Research Areas * Low-latency tool-calling architectures: Compact models optimized for response time * Efficient tool selection and delegation across model hierarchies. * Test-time observational learning: Methods for agents to acquire task knowledge through observation of user behavior. * Comparative analysis against supervised fine-tuning approaches when labeled data is available. * Action safety classification: Real-time classification of agent-initiated actions to assess risk and determine when human approval is required. * Calibration of confidence thresholds for autonomous execution. * Structured representations for agent interaction: Compilation of web application structure (static assets, API schemas, interaction patterns) into formats optimized for agent parsing and execution across client-side and server-rendered environments. 💡 What You'll Do * Prototype new ways of working with LLMs in engineering workflows * Lead the research, design, and development of AI technologies that challenge conventional software practices and uncover new ways for engineers to build and collaborate. * You explore where LLMs behave in unexpected yet promising ways, especially in tasks like context retention, code reasoning, or agent behavior , and use those moments to uncover new AI-native workflows. 🌱 Who Thrives Here You operate well in cross-functional settings where research, design, and engineering inform each other continuously. You are comfortable iterating quickly, testing ideas in real systems, and adjusting course based on what you observe. You may have worked in applied research environments where scientists are embedded with designers and engineers throughout the product development process rather than siloed from it. ✨ Always find a way 🔮💎🍔⭐️