Careers

Are you passionate about applying machine learning, time series forecasting, and operations research to transform the delivery of heavy and bulky items for Amazon customers? Are you excited about working with large-scale operational data and developing models that drive real business impact? If so, the Amazon Extra Large (AMXL) Science team may be the right fit for you. AMXL is Amazon's specialized business for delivering heavy and bulky items — appliances, furniture, fitness equipment, and mattresses — with a premium customer experience that includes room-of-choice delivery, at-home installations, and assembly services. In this role, you will leverage large-scale operational data to develop and deploy predictive models and optimization solutions that solve real-world logistics and fulfillment challenges, partnering closely with scientists, engineers, and business stakeholders. Key job responsibilities Apply machine learning, statistical modeling, time series analysis, and operations research techniques to build solutions for delivery routing, capacity planning, demand forecasting, workforce scheduling, and network optimization Analyze large-scale historical and real-time operational data to surface efficiency patterns, bottlenecks, and emerging trends across the AMXL network Develop, validate, and deploy models that improve cost-to-serve and customer experience Partner with cross-functional teams to implement data-driven strategies and measure impact Build scalable, automated pipelines for data ingestion, feature engineering, model training, and validation Monitor deployed model performance and communicate results through clear reporting on key operational and business metrics About the team You'll be part of a small, collaborative team of scientists who move fast and care deeply about the problems they solve. A typical week might involve whiteboarding a new forecasting approach with a senior scientist, partnering with engineers to push a model into production, deep-diving into operational data to understand why a metric moved, or presenting your findings to business leaders who will act on them. The work is high-visibility and high-impact. The models you build will directly influence how millions of heavy and bulky items reach customers.

The AWS Neuron Science Team is looking for talented scientists to enhance our software stack, accelerating customer adoption of Trainium and Inferentia accelerators. In this role, you will work directly with external and internal customers to identify key adoption barriers and optimization opportunities. You'll collaborate closely with our engineering teams to implement innovative solutions and engage with academic and research communities to advance state-of-the-art ML systems. As part of a strategic growth area for AWS, you'll work alongside distinguished engineers and scientists in an exciting and impactful environment. We actively work on these areas: - AI for Systems: Developing and applying ML/RL approaches for kernel/code generation and optimization - Machine Learning Compiler: Creating advanced compiler techniques for ML workloads - System Robustness: Building tools for accuracy and reliability validation - Efficient Kernel Development: Designing high-performance kernels optimized for our ML accelerator architectures About the team AWS Neuron is the software of Trainium and Inferentia, the AWS Machine Learning chips. Inferentia delivers best-in-class ML inference performance at the lowest cost in the cloud to our AWS customers. Trainium is designed to deliver the best-in-class ML training performance at the lowest training cost in the cloud, and it’s all being enabled by AWS Neuron. Neuron is a Software that include ML compiler and native integration into popular ML frameworks. Our products are being used at scale with external customers like Anthropic and Databricks as well as internal customers like Alexa, Amazon Bedrocks, Amazon Robotics, Amazon Ads, Amazon Rekognition and many more.

Amazon Robotics Vulcan is a robotic stowing system that uses a robot arm with a custom end-of-arm tool to place customer items into fulfillment center storage bins, alongside human associates. We operate in live fulfillment centers today and are scaling to additional sites globally. The Vulcan Motion team owns the motion stack that makes every interaction between the robot and the bin safe, fast, and predictable: real-time force-controlled manipulation, motion planning for insert and retract behaviors, compliant contact behaviors, and the safety envelope around all of it. We have many areas that need experienced scientists to drive from prototype to deployment at a global scale. For example: the framework our team uses to design, benchmark, and select controllers for each contact-rich behavior; the long-term controller roadmap with our industrial robot-arm vendors; the functional-safety envelope for live deployment; and the recovery architecture the robot uses when unexpected contact occurs. You may own one or two of these arcs depending on team needs and your strengths. This is a hands-on technical leadership role. You will write production C++ and Python, review code, and hold the technical bar on real-time control design selections that affect every cycle the robot executes. You will lead collaborations between our team and external partner teams in vision, hardware, and operations. Key job responsibilities - Research, propose, architect, and deliver complex features such as unified contact-control frameworks, robot-arm integration roadmaps, functional-safety envelopes, and motion recovery architectures. - Bring recent scientific advances in force control, compliant manipulation, and sim-to-real transfer into production. - Lead significant architectural and strategic initiatives together with more junior teammates. - Work across cross-disciplinary teams (hardware, safety, operations, vendor engineering) to deliver novel, synergistic features and capabilities. - Stay current with recent advances in robotics control, manipulation, and industrial automation. - Own the technical bar on real-time control design decisions and serve as the senior technical interface to external robot-arm engineering teams. A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! About the team Motion is one of several teams inside Amazon Robotics Vulcan. We ship weekly to live fulfillment centers, operate a fast iteration loop with real production data, and work across the full motion stack, from real-time controllers on hardware up through mission-level motion planning. We are looking for a senior Applied Scientist to help drive the next generation of robot behaviors alongside a strong existing team. If you want to go deep on controls problems, stay hands-on with hardware, and contribute to architectural direction, this role is for you.

Employer: Amazon Web Services, Inc. Position: Data Scientist II Location: Houston, TX Multiple Positions Available: Design and implement scalable and reliable approaches to support or automate decision making throughout the business. Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult business problems and cases in which the solution approach is unclear. Acquire data by building the necessary SQL / ETL queries. Import processes through various company specific interfaces for accessing Oracle, RedShift, and Spark storage systems. Build relationships with stakeholders and counterparts. Analyze data for trends and input validity by inspecting univariate distributions, exploring bivariate relationships, constructing appropriate transformations, and tracking down the source and meaning of anomalies. Build models using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing, machine learning algorithms, genetic algorithms, and neural networks. Validate models against alternative approaches, expected and observed outcome, and other business defined key performance indicators. Implement models that comply with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production. (40 hours / week, 8:00am-5:00pm, Salary Range $136000 - $184000) Amazon.com is an Equal Opportunity – Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation

The Alexa AI AURORA organization is seeking a passionate, talented, and resourceful Senior Data Scientist to define and solve complex, ambiguous problems in state-of-the-art conversational AI. You will lead large-scale data science initiatives across the fields of Large Language Models (LLMs), Natural Language Processing (NLP), and Artificial Intelligence (AI), selecting the ideal methodologies from a wide range of data science disciplines to drive measurable business impact for millions of Alexa customers. In this role, you will autonomously define problem spaces and solution approaches, working closely with business, science, and engineering teams to build consensus and influence strategy. You will advise senior leadership on data-driven decisions, identify blind spots in existing metrics, and propose new measurements that shape our product direction. You will actively mentor and develop other data scientists while setting standards for scientific rigor and operational excellence within the team. The ideal candidate has broad expertise across multiple data science disciplines and a deep understanding of how software systems, data pipelines, and business processes interact. They take the lead on complex projects with minimal guidance, make sound trade-offs between short-term customer needs and long-term technical investments, and deliver solutions that are scalable, reproducible, and actionable. A proven track record of launching data science solutions that drive significant business outcomes is essential. Strong communication skills, the ability to document and present technical findings to both technical and non-technical audiences, and a commitment to collaborative teamwork are absolute requirements. Join us in shaping the future of Generative AI and delivering unparalleled experiences for Alexa customers worldwide. Key job responsibilities Define the data science strategy for conversation modelling, content generation, and automated quality assurance by evaluating a wide range of methodologies across machine learning, generative AI, and computer vision, recommending the right approach based on business needs and scientific rigor. Lead the design and end-to-end delivery of complex, ambiguous data science initiatives from problem formulation through experimentation to production deployment, autonomously defining the problem space, selecting ideal solution approaches, and driving measurable business outcomes. Make high-judgment trade-offs across audio, text, and visual quality dimensions, balancing short-term customer needs against long-term platform extensibility, cost efficiency, and scalability while quantifying the impact of each decision. Establish evaluation frameworks, metrics, and success criteria for the team's scientific initiatives, identifying blind spots in existing measurements and proposing new mechanisms that institutionalize rigorous validation across customer touch points. Identify new business opportunities by staying at the forefront of AI/ML advances, translating emerging techniques into actionable data science directions with clear, quantifiable customer and business impact. Drive consensus across multiple teams on the architectural and methodological decisions underlying scalable agentic systems for conversation understanding and generation, ensuring alignment between data, software systems, and business processes. Set and continuously raise the bar for data science best practices across the team, creating models and analyses that are actionable, reproducible, and easy for others to contribute to and extend. Tackle the team's most complex technical problems, applying broad expertise across multiple data science disciplines while maintaining practical focus on solution generalizability and customer value. Actively mentor and develop other data scientists in the organization, leading scientific reviews, providing constructive feedback on methodology and results, and keeping the team current on data science advancements. Advance the team's scientific reputation through high-impact publications and presentations at top-tier venues, and generate intellectual property through patents. About the team AURORA is the AI runtime backbone and horizontal intelligence team that powers Alexa's core infrastructure, AI capabilities, and specialized conversational models. We revolutionize conversational AI through three core pillars: architecting mission-critical AI runtime systems, advancing science solutions that connect key conversational capabilities, and transforming how builders create at scale. We empower 1P and 3P engineers and scientists worldwide with modular, reusable platforms that accelerate innovation while delivering accurate, responsive, and reliable conversational experiences to millions of end-users through operational excellence at scale.

The candidate in this role will own delivery of science products and solutions to help Amazon Devices Sales and Marketing org. make better decisions: product recommendations to customers, segmentation, financial incrementality of marketing initiatives, A/B testing etc. Key job responsibilities The Amazon Devices organization designs, produces and markets Echo Speakers, Kindle e-readers, Fire Tablets, Fire TV Streaming Media Players, Ring and Blink Smart Home & Security products. We are constantly looking to innovate on behalf of customers with new devices in existing or new categories or improving customer experience on existing platforms. The Devices Data Services (DDS) team provides Data Science, Analytics and Engineering support to the broader organization to enable Sales and Marketing activities across all these product lines. We are looking for an innovative, hands-on and customer-obsessed Data Scientist who can be a strategic partner to the product managers and engineers on the team. Our projects span multiple organizations and require coordination of experimentation, economic and causal analysis, and building predictive machine learning models. A successful candidate will be a problem solver who enjoys diving into data, is excited by difficult modeling challenges, is motivated to build something that will eventually become a production software system, and possesses strong communication skills to effectively interface between technical and business teams. In this role, you will be a technical expert with massive impact. You will take the lead on developing advanced ML systems that are key to reaching our customers with the right recommendations at the right time. Your work will directly impact the success of Amazon's growing Devices business. You will work across diverse science/engineering/business teams. You will work on critical data science problems, building high quality, reliable, accurate, and consistent code sets that are aligned with our business needs. Key Performance Areas - Implement statistical or machine learning methods to solve specific business problems. - Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters. - Directly contribute to development of modern automated recommendation systems - Build customer-facing reporting tools to provide insights and metrics to track model performance and explain variance - Collaborate with researchers, software developers, and business leaders to define product requirements, provide analytical support, and communicate feedback A day in the life You will work with other scientists, engineers, product managers, and marketers to develop new products that benefit our customers and help us reach our business goals. You will own solutions from end to end: conceptualization, prioritization, development, delivery, and productionalization. About the team We are a full stack science team that empowers product, marketing, and other business leaders to better understand customers who use Amazon devices, make decisions on product development or optimization, and measure the effectiveness of their efforts against our customer’s expectation. Our focus area is to build analytical frameworks that help the organization either access data, better understand the decisions customers are making and why, or assess customer satisfaction.

Amazon is on a mission to redefine the future of automation — and we're looking for exceptional talent to help lead the way. We are building the next generation of advanced robotic systems that seamlessly blend cutting-edge AI, sophisticated control systems, and novel mechanical design to create adaptable, intelligent automation solutions capable of operating safely alongside humans in dynamic, real-world environments. At Amazon, we leverage the power of machine learning, artificial intelligence, and advanced robotics to solve some of the most complex operational challenges at a scale unlike anywhere else in the world. Our fleet of robots spans hundreds of facilities globally, working in sophisticated coordination to deliver on our promise of customer excellence — and we're just getting started. As a Sr. Scientist in Robot Navigation, you will be at the forefront of this transformation — architecting and delivering navigation systems that are intelligent, safe, and scalable. You will bring deep expertise in learning-based planning and control, a strong understanding of foundation models and their application to embodied agents, and as well as have in-depth understanding of control-theoretic approaches such as model predictive control (MPC)-based trajectory planning. You will develop navigation solutions that seamlessly blend data-driven intelligence with principled control-theoretic guarantees. Our vision is bold: to build navigation systems that allow robots to move fluidly and safely through dynamic environments — understanding context, anticipating change, and adapting in real time. You will lead research that bridges the gap between cutting-edge academic advances and production grade deployment, collaborating with world-class teams pushing the boundaries of robotic autonomy, manipulation, and human-robot interaction. Join us in building the next generation of intelligent navigation systems that will define the future of autonomous robotics at scale. Key job responsibilities - Design, develop, and deploy perception algorithms for robotics systems, including object detection, segmentation, tracking, depth estimation, and scene understanding - Lead research initiatives in computer vision, sensor fusion and 3D perception - Collaborate with cross-functional teams including robotics engineers, software engineers, and product managers to define and deliver perception capabilities - Drive end-to-end ownership of ML models — from data collection and labeling strategy to training, evaluation, and deployment - Mentor junior scientists and engineers; contribute to a culture of technical excellence - Define and track key metrics to measure perception system performance in real-world environments - Publish research findings in top-tier venues (CVPR, ICCV, ECCV, ICRA, NeurIPS, etc.) and contribute to patents A day in the life - Train ML models for deployment in simulation and real-world robots, identify and document their limitations post-deployment - Drive technical discussions within your team and with key stakeholders to develop innovative solutions to address identified limitations - Actively contribute to brainstorming sessions on adjacent topics, bringing fresh perspectives that help peers grow and succeed — and in doing so, build lasting trust across the team - Mentor team members while maintaining significant hands-on contribution to technical solutions About the team Our team is a group is a diverse group of scientists and engineers passionate about building intelligent machines. We value curiosity, rigor, and a bias for action. We believe in learning from failure and iterating quickly toward solutions that matter.

MULTIPLE POSITIONS AVAILABLE Employer: AMAZON.COM SERVICES LLC Offered Position: Economist III Job Location: Boston, Massachusetts Job Number: AMZ9898444 Position Responsibilities: Mentor and guide the applied scientists and economists in our organization and hold us to a high standard of technical rigor and excellence in science. Design and lead roadmaps for complex science projects to help SP have a delightful selling experience while creating long term value for our shoppers. Work with our engineering partners and draw upon your experience to meet latency and other system constraints. Identify untapped, high-risk technical and scientific directions, and simulate new research directions that you will drive to completion and deliver. Be responsible for communicating our science innovations to the broader internal & external scientific community. Position Requirements: Ph.D. or foreign equivalent degree in Economics or a related field and two years of research or work experience in the job offered or a related occupation. Must have two years of research or work experience in the following skill(s): 1) experience in econometrics including experience with program evaluation, forecasting, time series, panel data, or high dimensional problems; 2) experience with economic theory and quantitative methods; and 3) coding in a scripting language such as R, Python, or similar. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation. 40 hours / week, 8:00am-5:00pm, Salary Range $159,200/year to $215,300/year. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit: https://www.aboutamazon.com/workplace/employee-benefits.#0000

Applied Scientists in AWS Automated Reasoning are dedicated to making AWS the best computing service in the world for customers who require advanced and rigorous solutions for automated reasoning, privacy, and sovereignty. Key job responsibilities - Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation. - Own strategic problem solving, and take the lead on the design, implementation, and delivery for solutions that have a long-term quantifiable impact. - Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience. - Develop strategic plans to identify fundamentally new solutions for business problems. - Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues.

Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the limits. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As an Applied Scientist on our team, you will focus on building state-of-the-art ML models for biology. Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams. Key job responsibilities - Build, adapt and evaluate ML models for life sciences applications - Collaborate with a cross-functional team of ML scientists, biologists, software engineers and product managers