Careers

Amazon.com’s Product Detail Page team is looking for talented, motivated and passionate applied scientist to be part of the design and development of a highly scalable multi-tiered shopping application to provide the best possible online shopping experience for Amazon customers world-wide. Our team is comprised of talented applied scientists, developers, testers, program managers, designers and product managers tasked with the singular goal to create THE world's best buying experience. Scientists on this team develop the next-generation technologies and experiences that change how millions interact and shop online. To provide the best possible online shopping at the scale of the web requires ideas from every area of computer science, including distributed computing, large-scale system design, machine learning, natural language processing, data compression and user interface design; the list goes on and is growing every day. We need our scientists to be versatile and always eager to tackle new problems as we continue to push technology forward. Our team leverages sophisticated econometric, machine learning, and big data technologies to help customers to discover the right products at the right prices from millions of trusted sellers billions of times a day. If you are looking for a career-defining opportunity on one of the most customer centric and business impacting teams within Amazon, we’d love to hear from you. We are looking for a Senior Applied Scientist to help build the next generation of Detail Page optimization algorithms. These new set of algorithms will incorporate the continually changing preferences of our customers and continue to scale with numerous new programs that Amazon is introducing for our customers. You will work with multiple Amazon businesses and programs to identify big business opportunities and propose new business features and technical systems to improve customer experience on Amazon Detail Page, Search Page and many other widgets throughout the website. You will be responsible for the quality of algorithm design and will get the opportunity to present your ideas and share results of your deliverables with Amazon executives on a frequent basis. You will get an opportunity to work with senior scientists to define and enforce broad, company-wide technical standards in optimization techniques, statistical modeling and simulation techniques, and/or data analytics.

Alexa AI is looking for a Senior Applied Scientist to build Alexa+, Amazon's LLM-powered conversational assistant. You will work on key initiatives spanning large language model fine-tuning, alignment, agentic reasoning, and evaluation — directly shaping the experience for hundreds of millions of customers worldwide. As a Senior Applied Scientist, you are a strong technical contributor who independently drives complex projects from ideation to production. You design and run rigorous experiments, develop novel approaches to challenging problems, and deliver high-quality models and systems at scale. Your work is characterized by scientific rigor, engineering excellence, and a focus on measurable customer impact. You collaborate effectively across teams, contribute to scientific discussions and reviews, and help elevate the technical bar within the organization. You proactively identify opportunities, propose solutions, and influence technical direction within your project area. Basic Qualifications - PhD/MS in Computer Science, Electrical Engineering, Machine Learning, Natural Language Processing, or a related technical field, OR Master's degree with 5+ years of relevant industry experience - 3+ years of hands-on experience in applied machine learning, predictive modeling, or NLP - Strong programming skills in Python or a related language - Experience with deep learning frameworks (e.g., PyTorch, TensorFlow) - Track record of delivering ML/NLP solutions from research to production - Experience working with large language models (training, fine-tuning, or evaluation) Preferred Qualifications - 5+ years of relevant industry or academic research experience - Experience with LLM alignment techniques (RLHF, DPO, constitutional AI) - Experience with agentic AI systems, including planning, tool use, and orchestration - Experience with distributed training and large-scale model optimization - Peer-reviewed publications at top-tier venues (e.g., NeurIPS, ICML, ACL, EMNLP, ICLR) - Strong communication skills with the ability to present complex technical concepts to diverse audiences - Experience mentoring junior scientists or engineers Key job responsibilities - Design, implement, and evaluate novel approaches to LLM fine-tuning, alignment (RLHF, DPO), and distillation for production deployment - Develop and improve agentic systems — including multi-step reasoning, tool use, planning, and orchestration — that work reliably at scale - Build evaluation frameworks and methodologies that go beyond standard benchmarks to capture real-world conversational quality - Translate research advances into customer-facing products, working closely with engineering, product, and cross-functional science teams - Analyze large-scale experimental results, identify patterns, and iterate rapidly on model improvements - Publish results at top-tier venues and contribute to Amazon's presence in the broader research community - Mentor junior scientists and contribute to hiring efforts About the team Alexa AI is building the science and technology behind Alexa+, Amazon's next-generation conversational assistant. Our team works at the intersection of large language models, reinforcement learning from human feedback and verifiable rewards, agentic architectures, and multilingual/multimodal understanding. We operate at massive scale — our models serve customers across dozens of languages and device types. If you want to push the frontier of conversational AI and see your work used by people every day, come join us.

Join our Frontier AI & Robotics team to support the development of test infrastructure for next-generation robotic systems that will transform how robots perceive and interact with the world. You'll take ownership of designing and implementing software-driven test and validation frameworks across advanced actuators, precision sensors, and robotic subsystems — ensuring engineering validation and manufacturing test readiness to support breakthrough AI research and real-world deployment. Key job responsibilities - Test Infrastructure Development - Design, develop, and maintain automated test frameworks for engineering validation and manufacturing test of robotic systems and subsystems. Build scalable, reusable test software that integrates with hardware-in-the-loop (HIL) environments, data acquisition systems, and robotic control interfaces. - Software Integration & Automation - Develop test automation software in Python, C++, or equivalent languages to exercise actuators, sensors, vision systems, and communication interfaces. Implement scripted test sequences, data logging pipelines, and pass/fail criteria for prototype and production-intent hardware. - Hardware Bring-Up & SW/HW Integration - Perform hands-on hardware bring-up of robotic subsystems including power sequencing, communication interface validation, peripheral initialization, and firmware/software integration. Debug across the full stack, from board-level hardware through embedded firmware to application-layer test software, to bring new hardware revisions to a validated, testable state. - Engineering Validation & Mfg Test - Create and execute test protocols for functional validation, performance characterization, and regression testing of robotic subsystems. Develop test stations and software tooling that transition from R&D validation through manufacturing test readiness. - Debugging & Failure Analysis - Troubleshoot and root-cause issues across the robotic platform (power, compute, comms, actuators, sensors) using software diagnostic tools, log analysis, and bench instrumentation. Conduct failure analysis from component to system level. Reproduce critical failures and bridge communication between the lab and engineering teams. - Data Analysis & Reporting - Build data pipelines and analysis tools to aggregate test results, identify trends, and generate automated test reports. Develop dashboards or visualization tools that provide engineering teams with actionable insights on hardware quality and reliability. - Technical Documentation - Author and maintain test plans, test procedures, automation framework documentation, failure analysis reports, and troubleshooting guides; uphold consistent documentation standards across the lab. - Lab Operations Support - Support equipment maintenance, inventory management, vendor coordination, and safety/regulatory compliance for test lab environments. A day in the life Your focus centers on the software test infrastructure and hardware integration that validates our advanced robotic platforms. You'll develop and maintain automated test systems for engineering validation and manufacturing test while getting hands-on with hardware bring-up and debugging, working alongside hardware engineers, firmware developers, and fellow technicians. Your responsibilities include writing test automation code, building HIL test environments, bringing up new hardware revisions, debugging SW/HW integration issues at the bench, analyzing test data, and designing test fixtures. Throughout the day, you balance developing new test capabilities with hands-on hardware integration, supporting urgent prototype bring-up requests, maintaining test infrastructure, and preparing test readiness for upcoming milestones. You're switching between writing code at your workstation, probing signals and validating hardware at the bench, collaborating in design reviews with engineers, and ensuring test lab equipment is calibrated and maintained. About the team At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up. Our team is building the future of intelligent robotics through frontier foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact. We leverage Amazon's computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios. We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.

Alexa Smart Home Science builds the intelligence that lets customers control and automate their homes naturally, spanning voice understanding, proactive automation, habit and preference learning, and the LLM/agentic systems that power the next generation of ambient home experiences. We are looking for a Senior Applied Scientist to own the scientific direction of a major workstream, turning ambiguous, open-ended problems into production systems that measurably improve the customer experience across millions of homes. You will define the research agenda for your area, partner deeply with engineering to bring models into production, and raise the scientific bar across the broader team. You will work at the intersection of large language models, agentic orchestration, personalization, and real-world heterogeneity across homes, devices, and occupants. This is a hands-on role: you will frame the problems, build the models, guide the system design, and mentor other scientists, while influencing product and technical roadmaps beyond your immediate team. Key job responsibilities - Independently identify, frame, and solve ill-defined research problems tied to broad Smart Home problem areas, delivering with limited guidance. - Define system-level technical requirements and partner with engineering teams to adapt scientific techniques to meet production constraints (latency, cost, reliability), making appropriate tradeoffs. - Own the science strategy and roadmap for a workstream; anticipate future business and technical requirements. - Design and run rigorous experimentation and evaluation to validate approaches and quantify customer/business impact. - Build consensus on scientific approach and best practices across multiple teams; influence product features and technical direction beyond your own team. - Actively mentor and develop other scientists, and raise the bar in hiring. - Contribute to the internal and external scientific community through publications, patents, and dissemination of scientific artifacts. A day in the life No two days look alike, but the throughline is owning a scientific problem from question to production impact. You might dig into evaluation results to find where the experience falls short, frame a hypothesis, and prototype with LLMs or agentic techniques. You will pair with engineering to turn a promising model into a production-ready design, weighing latency, cost, and reliability tradeoffs. Expect alignment with product managers on customer problems, working sessions with fellow scientists, and time mentoring teammates. Your customers are Alexa smart home users across millions of households; your stakeholders span product, engineering, and partner science teams. About the team We are the science team behind Alexa's smart home experience. We are applied scientists and science engineers making the home genuinely intelligent: anticipatory, personalized, and effortless. Our mission is to move Alexa from reacting to commands toward understanding a household's rhythms and acting helpfully on the customer's behalf, reliably and at scale. Because no two homes are alike, we embrace that diversity rather than paper over it. We value research-grounded decisions, hands-on work, and long-horizon bets. Scientists own their areas end-to-end, mentor one another, publish, and partner closely with engineering and product.

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 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

At Amazon, we are working to be the most customer-centric company on earth, where customers can find and discover anything they might want to buy online. Our Supply Chain organization spans the entire Amazon fulfillment network, from inventory placement and capacity planning through middle mile and last mile delivery. Our goal is to build a world class, end-to-end supply chain that exceeds the expectations of our customers by ensuring their orders are delivered as quickly, accurately, and cost effectively as possible. We are now looking to hire a passionate, innovative and customer-obsessed candidate to support our end-to-end network planning and optimization across the Amazon supply chain. As an Applied Scientist, you will work with software engineers, product managers and business teams to understand the requirements and current challenges, distill that understanding to elegantly define the problem, and develop innovative solutions that integrate planning and execution across the entire fulfillment pipe. A central part of this mission is harnessing recent advances in Artificial Intelligence, including machine learning, large language models, and generative AI, to transform how we optimize the network and make decisions at scale. Key job responsibilities • Solve complex optimization and machine learning problems using scalable algorithmic techniques. • Apply modern AI methods, including generative and foundation models, to improve optimization, forecasting, and automated decision making across the supply chain. • Design and develop efficient research prototypes that address real-world problems across Amazon's end-to-end supply chain operations. • Lead complex time-bound, long-term as well as ad-hoc analyses to assist decision making. • Communicate to leadership results from business analysis, strategies and tactics, including how AI-driven approaches change the way decisions are made. A day in the life The role will own the approval from senior functional leaders to enable strategies that improve processes and performance across the supply chain. You will be a natural self-starter who is comfortable supporting complex cross functional projects and action plans. You will have a true hands-on approach, the ability to generate solutions, strong process management skills, and be an effective communicator.

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.

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'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.