Careers

Are you a MS or PhD student interested in a 2026 internship in the field of machine learning, deep learning, generative AI, large language models and speech technology, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods? If so, we want to hear from you! We are looking for students interested in using a variety of domain expertise to invent, design and implement state-of-the-art solutions for never-before-solved problems. You can find more information about the Amazon Science community as well as our interview process via the links below; https://www.amazon.science/ https://amazon.jobs/content/en/career-programs/university/science https://amazon.jobs/content/en/how-we-hire/university-roles/applied-science Key job responsibilities As an Applied Science Intern, you will own the design and development of end-to-end systems. You’ll have the opportunity to write technical white papers, create roadmaps and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists and other science interns to develop solutions and deploy them into production. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon’s customer focused culture. The ideal intern must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. A day in the life At Amazon, you will grow into the high impact person you know you’re ready to be. Every day will be filled with developing new skills and achieving personal growth. How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow. Some more benefits of an Amazon Science internship include; • All of our internships offer a competitive stipend/salary • Interns are paired with an experienced manager and mentor(s) • Interns receive invitations to different events such as intern program initiatives or site events • Interns can build their professional and personal network with other Amazon Scientists • Interns can potentially publish work at top tier conferences each year About the team Applicants will be reviewed on a rolling basis and are assigned to teams aligned with their research interests and experience prior to interviews. Start dates are available throughout the year and durations can vary in length from 3-6 months for full time internships. This role may available across multiple locations in the EMEA region (Austria, Estonia, France, Germany, Ireland, Israel, Italy, Jordan, Luxembourg, Netherlands, Poland, Romania, Spain, South Africa, UAE, and UK). Please note these are not remote internships.

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

Join the Personal Robotics Group at Amazon, where you'll help pioneer intelligent robotic products that deliver meaningful customer experiences. As a Senior Applied Scientist, you'll lead the development of advanced control systems that enable robots to operate naturally, safely, and intelligently in complex real-world environments. You'll drive technical excellence in areas such as RL-based locomotion policies, whole-body manipulation, sim-to-real transfer, vision-aided control, and safe human-robot interaction. In this role, you'll combine hands-on technical work with scientific leadership, developing robust control solutions that enable robots to perform complex loco-manipulation tasks in dynamic environments. You'll leverage Amazon's computational resources and robotics infrastructure to tackle ambitious robotics problems. Key job responsibilities - Lead technical initiatives in whole-body control and locomotion, driving breakthrough approaches through hands-on research and development in areas including policy learning, natural motion generation, vision-aided locomotion, and loco-manipulation - Design and implement novel RL architectures and training paradigms for robust whole-body control that enables complex tasks across diverse scenarios - Develop sim-to-real transfer techniques that enable policies trained in simulation to perform reliably on physical hardware - Guide technical direction for locomotion and control projects from research through deployment, ensuring robust performance in real-world environments - Collaborate with navigation, manipulation, and hardware teams to ensure seamless integration of whole-body control with perception and planning systems - Mentor fellow scientists and engineers while maintaining strong individual technical contributions - Establish benchmarks and evaluation frameworks for measuring locomotion and whole-body control performance across simulation and on-device testing About the team The Personal Robotics Group is pioneering intelligent robotic products that deliver meaningful customer experiences. We're building the next generation of robotic systems that will redefine how customers interact with technology. This is a unique opportunity to shape the future of personal robotics working with world-class teams pushing the boundaries of what's possible in robotic manipulation, locomotion, and human-robot interaction. Join us if you’re passionate about creating the future of personal robotics, solving complex challenges at the intersection of hardware and software, and seeing your innovation deliver transformative customer experiences.

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.

Amazon is looking for creative Applied Scientists to tackle some of the most interesting problems in Artificial Intelligence (AI), natural language processing (NLP), knowledge graph curation, search, recommendation and related areas with our Amazon Books team. At Amazon Books we believe that reading is essential for a healthy society. As such, we aim to inspire readers by making it easy to read more and get more out of reading. We do this by creating an unmatched book discovery experience for our customers worldwide. We enable customers to discover new books, authors and genres through smart search tools, intelligent interactions and sophisticated recommendations, and we need your help to keep innovating in this space. If you are looking for an opportunity to solve deep technical problems and build innovative solutions in a fast-paced environment working within a smart and passionate team, this might be the role for you. You will develop and implement novel algorithms, agentic systems and modeling techniques to advance the state-of-the-art in technology areas at the intersection of AI, LLMs, NLP, search, and deep learning. You will innovate at scale, help move the needle for research in these exciting areas and build state-of-the-art technologies that enable delightful experiences for hundreds of millions of people. Key job responsibilities In this role you will: - Work collaboratively with other scientists and developers to design and implement scalable and reliable pipelines for ensuring our vast knowledge base of books meets the highest levels of accuracy and is aligned with how customers think about books; - set the scientific roadmap needed to sustain state-of-the-art quality and efficiency. Stay up-to-date with the latest technologies and adopt the most appropriate long-term solution to a variety of use cases. - set the standard for science rigor and quality, deal with ambiguity and competing objectives, and mentor other members to achieve their career growth potential. - Drive scalable solutions: from understanding the customer and business needs, to prototyping, production testing and through engineering directly to production. A day in the life Day-to-day work varies, but on a typical day you will: - run (or supervise) experiments. Depending on the stage or project, this may involve designing the experiments, collecting data, training models, prompt/spec engineering/optimization, error analysis, online system analysis, etc. - drive decisions by interpreting and communicating experimental results with stakeholders (managers, subject matter experts, other scientists, and engineers) and seeking/listening to their feedback. - strategic thinking: review results, identify trends and what step-changes are needed. You'll contribute to regular meetings, activities and conferences with the wider science team, organization as well as internal and external communities. About the team The team consists of a collaborative group of scientists, product leaders, and dedicated engineering teams. Our aim is to maintain the world’s most accurate and descriptive set of books metadata, where every title in our catalog is uniquely characterized via a set of high-quality, concise attributes. We believe this is a foundational capacity for any bookstore. We work with sister teams to leverage our systems to drive a diverse array of customer experiences, owned both by ourselves and others, that enable customers to easily identify their ideal next read.

The R2L team is responsible for building the next generation supply chain for Amazon’s world-class ultra-fast customer experiences including Amazon Fresh groceries, Sub-Same Day, Amazon Now, and other soon-to-launch exciting new businesses. Join us and you'll be taking part in serving our customers in as fast as 30 minutes! We are looking for a Data Scientist to join our team and solve some of the most complex business problems! Key job responsibilities - Work with product managers, engineers, other scientists, and leadership to identify and prioritize complex problems. - Interview stakeholders to gather business requirements and translate business problems into data science or analytical problems - Design, develop, and evaluate highly innovative statistics and ML models - Guide and establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation - Proactively seek to identify business opportunities and insights and provide solutions to shape key business processes and policies based on a broad and deep knowledge of Amazon data, industry best-practices, and work done by other teams. A day in the life In this role, you will be a technical expert with significant scope and impact. You will work with Product and Supply Chain Managers, Business Intelligence Engineers, System Developers and other Scientists, to develop models that solve a wide range of complex and ambiguous business problems, with the main goal to improve customer experience, improve availability of products and reduce supply chain cost. A successful Data Scientist will have bias for action needed in a startup environment, with great leadership skills, proven ability to build and manage medium-scale modeling projects, identify data requirements, build methodology and tools that are statistically grounded. It will be a person who enjoys diving deep into data, doing analysis, discovering root causes, and designing long-term scientific solutions. We are seeking someone who can thrive in a fast-paced, high-energy and fun work environment where we deliver value incrementally and frequently. We look for individuals who know how to deliver results and show a desire to develop themselves, their colleagues, and their career. About the team The R2L team is responsible for building the next generation supply chain for Amazon’s world-class ultra-fast customer experiences including Amazon Fresh groceries, Sub-Same Day, Amazon Now, and other soon-to-launch exciting new businesses. Join us and you'll be taking part in serving our customers in as fast as 30 minutes!

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.

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 🔮💎🍔⭐️