Careers

Amazon Music is an immersive audio entertainment service that deepens connections between fans, artists, and creators. From personalized music playlists to exclusive podcasts, concert livestreams to artist merch, Amazon Music is innovating at some of the most exciting intersections of music and culture. We offer experiences that serve all listeners with our different tiers of service: Prime members get access to all the music in shuffle mode, and top ad-free podcasts, included with their membership; customers can upgrade to Amazon Music Unlimited for unlimited, on-demand access to 100 million songs, including millions in HD, Ultra HD, and spatial audio; and anyone can listen for free by downloading the Amazon Music app or via Alexa-enabled devices. Join us for the opportunity to influence how Amazon Music engages fans, artists, and creators on a global scale. Amazon Music - Search Science team is seeking an experienced Applied Scientist who will join a team of experts in the field of machine learning, and work together to break new ground in the world of understanding and classifying different forms of music, and creating interactive experiences to help users find the music they are in the mood for. We work on machine learning problems for music classification, recommender systems, dialogue systems, NLP, and music information retrieval. You'll work in a collaborative environment where you can pursue applied research, with many peta-bytes of data, work on problems that haven’t been solved before, quickly implement and deploy your algorithmic ideas at scale, understand whether they succeed via statistically relevant experiments across millions of customers, and publish your research. You'll see the work you do directly improve the experience of Amazon Music customers on Alexa/Echo, mobile, and web. Key job responsibilities - Use machine learning, deep learning, LLMs and Agentic AI techniques to create scalable solutions for business problems - Analyze and extract relevant information from large amounts of Amazon's data to help automate and optimize key processes - Design, development and evaluation of AI models for predictive learning - Work closely with software engineering teams to drive model implementations and new feature creations - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation - Research and implement novel machine learning and statistical approaches About the team Everyone on our team has a meaningful impact on product features, new directions in music streaming, and customer engagement. We are looking for new team members across a variety of job functions including software engineering/development, marketing, design, ops and more. Come join us as we make history by launching exciting new projects in the coming year.Our team is focused on building a personalized, curated, and seamless music experience. We want to help our customers discover up-and-coming artists, while also having access to their favorite established musicians. We build systems that are distributed on a large scale, spanning our music apps, web player, and voice-forward audio engagement on mobile and Amazon Echo devices, powered by Alexa to support our customer base. Amazon Music offerings are available in countries around the world, and our applications support our mission of delivering music to customers in new and exciting ways that enhance their day-to-day lives.

We are seeking a Sr. Applied Scientist to develop and optimize Visual Inertial Odometry (VIO) and sensor fusion systems for our intelligent robots. In this role, you will design, implement, and deploy state estimation and tracking algorithms that enable robots to understand their position and motion in real time, even in challenging and dynamic environments. You will own the full pipeline from algorithm development through embedded deployment, ensuring that perception systems run efficiently on resource-constrained robotic hardware. You will also leverage modern machine learning approaches to push the boundaries of classical perception methods, combining learned representations with geometric techniques to achieve robust, real-time performance. This is a deeply hands-on role. You will work directly with sensors, hardware, and real-world data, while prototyping, testing, and iterating in physical environments. The ideal candidate has strong foundations in VIO and sensor fusion, practical experience optimizing algorithms for embedded platforms, and familiarity with how modern deep learning is transforming perception. Key job responsibilities - Design and implement Visual Inertial Odometry algorithms for robust real-time state estimation on robotic platforms like Sprout - Develop multi-sensor fusion pipelines integrating cameras, IMUs, and other sensing modalities for accurate pose tracking - Optimize perception and tracking algorithms for deployment on embedded hardware (e.g., ARM, GPU-accelerated edge devices) under strict latency and power constraints - Apply modern ML-based perception techniques (learned features, depth estimation, neural odometry) to complement and improve classical geometric approaches - Build and maintain calibration, evaluation, and benchmarking infrastructure for perception systems - Collaborate with hardware, controls, and navigation teams to integrate perception outputs into the robot’s autonomy stack - Lead technical projects from research prototyping through production deployment

Here at Amazon, we embrace our differences. We are committed to furthering our culture of diversity and inclusion of our teams within the organization. We’re working on the future. If you are seeking an iterative fast-paced environment where you can drive innovation, apply state-of-the-art technologies to solve large-scale real world challenges and provide visible benefit to end users, this is your opportunity. Come work for the Amazon Prime Air team! We're looking for an Applied Scientist who combines deep expertise in formal methods and software verification with a demonstrated ability to take research techniques from prototype to production. This person must be comfortable working alongside software engineers building safety-critical drone systems and collaborating with researchers pushing the boundaries of automated reasoning. We're looking for someone who can apply model checking, symbolic execution, and AI-guided test generation to find defects that sampling-based verification cannot catch. You will work hard, have fun, and of course, make history! Export Control License This position may require a deemed export control license for compliance with applicable laws and regulations. Placement is contingent on Amazon’s ability to apply for and obtain an export control license on your behalf.

Within Amazon's North American Operations, we are tackling mission-critical problems that center on improving employee safety and productivity. We build complex causal, forecasting, and optimization models to understand, predict, and optimize our network operations. We are seeking an Applied Scientist to drive the operational excellence of these models, deeply integrate across Amazon systems, and leverage generative AI to more intelligently build for our customers. Key job responsibilities - Interfacing with stakeholders to understand business problems and translating these into high and low-level design documents. - Architecting, building, and deploying production-grade models to cloud-native environments, incorporating CI/CD best practices. - Designing AI systems to provide model explainability, as well as automate customer workflows. - Developing evaluation frameworks for models that identify quality regressions before customers do. A day in the life You will be a single-threaded owner of projects within Amazon Operations, owning project scoping, stakeholder engagement, data enablement, model development, and production launches. Your work will be directly consumed by partner teams throughout Operations and Finance, and hence a strong sense of ownership is required to educate both technical and non-technical stakeholders on developed science solutions. About the team Our team is comprised of Data Scientists, Applied Scientists, and Economists, and are trusted to make data-driven solutions that power operations decision making. We strive to build consensus on divisive topics through clear presentation of problem statements paired with deep analyses that gain visibility throughout all levels of the organization from operators to executives.

Amazon's Global Procurement Organization is on a mission to transform how procurement works at Amazon scale. We build the technology that powers billions of dollars in purchasing decisions, and We're looking for an Applied Scientist to lead the delivery of science driven solutions focused on procurement of non-inventory supplies across Amazon's global operations. This is a high-impact role at the intersection of technology, operations, and business strategy — where your work directly influences how Amazon procures and manages supplies at scale. Key job responsibilities As an Applied Scientist in our team, you will be responsible for the research, design, and development of new AI technologies for Procurement. You will adopt or invent new machine learning and analytical techniques in the realm of forecasting, information retrieval and large language models. You will collaborate with scientists, engineers, and product partners locally and abroad. Your work will include inventing, experimenting with, and launching new features, products and systems.

We are seeking a Senior Applied Scientist to build production machine learning systems that solve complex business problems at scale. You will design, develop, and deploy ML solutions that directly impact millions of users and drive strategic decision-making across the organization. In this role, you will work on challenging problems spanning predictive modeling, natural language processing, recommendation systems, and generative AI applications. You will collaborate with cross-functional teams to translate ambiguous business challenges into rigorous technical solutions. Key job responsibilities - Design and deploy large-scale machine learning systems in production environments - Develop innovative ML solutions using state-of-the-art techniques including deep learning, NLP, and generative AI - Create ML solutions that personalize manager onboarding and development experiences — identifying individual capability gaps, recommending tailored learning pathways, and measuring development effectiveness across diverse manager populations and contexts - Partner to build causal inference models and experimental frameworks to measure impact - Collaborate with product managers, engineers, and business leaders to define technical roadmaps - Communicate complex technical concepts to diverse audiences, from technical peers to senior leadership About the team The People eXperience and Technology Central Science Team (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. We are an interdisciplinary team that combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal.

Amazon is looking for a passionate and inventive scientist to advance the science in foundational models and Agentic AI. Specifically, as part of our science team in Amazon AWS Agentic AI, you will lead the research and development of techniques for efficient and effective Agent optimization/learning, through various techniques ranging from model fine-tuning (e.g. RL) to context optimization, as a foundational layer for AWS customers to build reliable and performant Agents. You will have the opportunity to take a product from zero to one by influencing directly the product and science roadmap, and impact millions of our customers. You will also gain hands on experience with Amazon’s large-scale computing resources to accelerate advances in foundation models. Key job responsibilities * Develop short-term and long-term science roadmap for research in the broad area of Agent optimization/learning, which could range from RL reward shaping, training efficiency optimization, to automatic prompt optimization and techniques to learn from agent memory. * Develop concrete science plan, implement and validate research idea before moving it to production * Collaborate across product and engineering teams to transfer science innovations into AWS customer facing product. About the team Diverse Experiences AWS 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 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 Here at AWS, 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) 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 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 in the cloud.

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced ML systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real-world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning team for India Consumer Businesses. Machine Learning, Big Data and related quantitative sciences have been strategic to Amazon from the early years. Amazon has been a pioneer in areas such as recommendation engines, ecommerce fraud detection and large-scale optimization of fulfillment center operations. As Amazon has rapidly grown and diversified, the opportunity for applying machine learning has exploded. We have a very broad collection of practical problems where machine learning systems can dramatically improve the customer experience, reduce cost, and drive speed and automation. These include product bundle recommendations for millions of products, safeguarding financial transactions across by building the risk models, improving catalog quality via extracting product attribute values from structured/unstructured data for millions of products, enhancing address quality by powering customer suggestions We are developing state-of-the-art machine learning solutions to accelerate the Amazon India growth story. Amazon India is an exciting place to be at for a machine learning practitioner. We have the eagerness of a fresh startup to absorb machine learning solutions, and the scale of a mature firm to help support their development at the same time. As part of the India Machine Learning team, you will get to work alongside brilliant minds motivated to solve real-world machine learning problems that make a difference to millions of our customers. We encourage thought leadership and blue ocean thinking in ML. Key job responsibilities Use machine learning and analytical techniques to create scalable solutions for business problems Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate 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 Work closely with business partners to identify problems and propose machine learning solutions Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model maintenance Work proactively with engineering teams and product managers to evangelize new algorithms and drive the implementation of large-scale complex ML models in production Leading projects and mentoring other scientists, engineers in the use of ML techniques About the team International Machine Learning Team is responsible for building novel ML solutions that attack India first (and other Emerging Markets across MENA and LatAm) problems and impact the bottom-line and top-line of India business. Learn more about our team from https://www.amazon.science/working-at-amazon/how-rajeev-rastogis-machine-learning-team-in-india-develops-innovations-for-customers-worldwide

We are seeking an Applied Scientist II to work on development of an AI-based data intelligence and classification platform that will redefine how security and privacy assessments and enforcement are conducted at scale. This mission-critical platform will leverage AI-driven autonomous agents to conduct proactive, intelligent security operations across the company. The platform will integrate deeply with internal security, privacy, engineering, and cloud-native tools to provide self-serve, automated insights, verifications, and enforcement mechanisms. This role requires strong technical expertise in AI/ML, LLMs, and distributed cloud infrastructure, as well as thought leadership to drive alignment across multiple teams, customers, and business units. This is an opportunity to shape the future of AI-driven security and privacy assurance at an enterprise scale, defining standards, influencing company-wide security posture, and leading technical innovation at the highest level. Key job responsibilities * Architect and define the next-generation data classification and search matching platform, leading the technical strategy for AI-driven security automation across applied science and engineering teams * Build on multi-agent LLM framework, and influence your organizations in adopting the promising approaches * Develop a highly scalable, traditional ML-based as well as LLM-based intelligent security agent framework that enables internal teams to automate processing of structured and unstructured data * Combine depth and breadth of domain expertise and provide technical leadership to the entire team while also doing hands-on work by diving deep into details to diagnose complex system performance problems. About the team The Data Categorization team helps Amazonians understand their data and govern it at scale and ensures experiences delivered by Amazon to our customers uphold our high security and privacy standards. The science team harnesses AI to strengthen Amazon’s privacy and security posture more efficiently and effectively.

We are seeking a Member of Technical Staff — Mechanical Engineer to lead the structural and electromechanical design of advanced high degree-of-freedom robotic systems within a frontier AI and robotics research lab. You will own the mechanical architecture of our robotics platform end-to-end: actuator selection, joint design, thermal management, cable routing, sensing integration, and structural optimization — all under the demanding constraints of a high-DoF system that must be lightweight, robust, and production-viable. This is a unique opportunity to define the physical design direction of a next-generation robotics platform from first principles. The ideal candidate has deep experience designing complex robotic systems and scaling hardware from concept through prototyping to production. You thrive on analytical problem solving, possess strong intuition for structural and electromechanical tradeoffs, and are equally comfortable in CAD and on the shop floor. You will be the technical lead of a small team of talented mechanical engineers while collaborating closely with electrical, firmware, controls, and AI research teams to set the mechanical and structural direction of the platform. Beyond core platform development, this role offers real latitude to push into novel territory — novel actuation methods, advanced sensor integration, or new approaches to mechatronic packaging. If you have research instincts alongside shipping discipline, you'll find an environment that rewards both. We're looking for someone who wants to be the technical authority on how a high-performance robot is physically built, not just a contributor to the effort. What You Bring: - A systems-thinking mindset with a strong grasp of cross-domain engineering tradeoffs. - A bias toward action: comfortable building, testing, and iterating rapidly. - A collaborative and communicative working style — especially in multi-disciplinary research environments. - A passion for robotics and advancing the state of the art in intelligent, capable machines. Key job responsibilities - Lead mechanical design of robotic subsystems and full platforms, including structures, joints, enclosures, and mechanisms for a research environment. - Own kinematic, dynamic, and structural analyses to guide the design and optimization of full systems and subsystems of high-DoF robots - Specify and integrate actuators and motors for high-torque density applications in high-degree-of-freedom systems. - Drive rapid iteration and prototyping cycles — from concept sketches through functional hardware — to accelerate learning and compress development timelines in a fast-paced R&D environment. - Partner with the AI research team to establish simulation pipelines that enable rapid exploration of mechanical design space, informing actuator choices, structural topology, and system-level tradeoffs before committing to physical builds. - Contribute to thermal management strategies for motors, sensors, and embedded compute hardware. - Integrate sensors such as lidar, stereo cameras, IMUs, tactile sensors, and compute modules into compact, functional assemblies. - Design and route cabling and wire harnesses, ensuring reliability, serviceability, and thermal/electrical integrity. - Prototype and test mechanical systems; support hands-on builds, debug sessions, and field testing. - Conduct root cause analysis on system-level failures or performance issues and implement design improvements. - Apply Design for Manufacturing (DFM) and Design for Assembly (DFA) principles to transition prototypes into scalable builds (10s–100s of units). - Collaborate with cross-functional teams in electrical engineering, controls, perception, and research to meet research and product goals. About the team Frontier AI & Robotics (FAR) is the team at Amazon building the next generation of embodied intelligence. FAR drives the development and implementation of advanced AI models within Amazon’s operations that enable robots to see, reason, and act on the world around them, supporting a number of different warehouse automation tasks.