Careers

Join Amazon's Last Mile Technology Revolution! Are you ready to reshape the future of logistics? Join us in transforming how millions of packages reach their final destination through state-of-the-art technology and innovation! The Last Mile Technology organization is pioneering advanced solutions that are revolutionizing Amazon Logistics (AMZL). Our mission is to create intelligent, efficient, and scalable systems that will transform the delivery experience. We're building the future of last-mile logistics while maintaining Amazon's highest standards for safety and reliability. The Last Mile challenge is a fascinating blend of real-world complexity and technological innovation. We're tackling multidimensional problems that involve enabling AI agents to perceive and navigate complex delivery environments, understanding dynamic scenes through visual data, and adapting to everything from unexpected obstacles to varying weather and lighting conditions – all while ensuring every package arrives safely as per our promise. As an Applied Scientist on our Last Mile Technology team, you'll be at the forefront of developing computer vision and perception systems that enable us to understand and interact with the physical world. You'll design and implement deep learning models for visual perception, build algorithms that enable decision-making, and create robust systems that allow AI agents to operate safely across diverse geographical areas. Your research must excel in environments ranging from dense urban centers to suburban neighborhoods, each presenting unique visual and navigational challenges that require innovative solutions in perception and control. What Makes This Role Exciting: Real-World Impact: Your computer vision models and control algorithms will power AI agents that deliver millions of packages to customers, making their lives better every day Scale That Matters: Develop perception systems that operate across thousands of delivery agents in different cities, weather conditions, lighting scenarios, and dynamic environments Innovation at Scale: Publish novel research and create entirely new approaches to visual perception, scene understanding, and control systems End-to-End Science: Work on complete solutions from object detection and tracking to path planning and control, from sim-to-real transfer to real-world deployment and continuous learning from agent experiences

The Amazon Center for Quantum Computing in Pasadena, CA, is looking to hire an Applied Scientist specializing in the design of microwave components for use in cryogenic environments. Working alongside other scientists and engineers, you will design and validate hardware performing microwave signal conditioning at cryogenic temperatures for Amazon quantum processors. Working effectively within a cross-functional team environment is critical. The ideal candidate will have a proven track record of hardware development from requirements development to validation. Diverse Experiences Amazon 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. 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. 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 (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship and 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. Key job responsibilities Our scientists and engineers collaborate across diverse teams and projects to offer state of the art, cost effective solutions for the signal conditioning of Amazon quantum processor systems at cryogenic temperatures. You’ll bring a passion for innovation, collaboration, and mentoring to: Solve layered technical problems across our cryogenic signal chain. Develop requirements with key system stakeholders, including quantum device, test and measurement, hardware, and theory teams. Design, implement, test, deploy, and maintain innovative solutions that meet both performance and cost metrics. Research enabling technologies necessary for Amazon reach commercial viability in quantum computing . A day in the life As you research, design, and implement cryogenic microwave signal conditioning solutions, you will also: Participate in requirements, design, and test reviews. Work cross-functionally to help drive decisions using your unique technical background and skill set. Define and maintain standards for operational excellence. Work in a high-paced, startup-like environment where you are provided the resources to innovate quickly.

Are you excited about building optimization models that directly impact how millions of packages reach Amazon customers faster and at lower cost? The SCOT Planning Optimization team is looking for a Data Scientist I to help shape the future of supply chain planning at Amazon. In this role, you will develop and enhance mathematical optimization models that generate the volume plan for North American network —determining how much inventory flows where, when, and how across hundreds of sites. Your work will focus not only on making these models optimal, but also explainable—ensuring stakeholders can understand and trust the decisions being made. You will build network plan simulations to evaluate scenarios and stress-test planning strategies before they go live. You'll be working at the frontier of Agentic and Generative AI, building intelligent agents that automate planning workflows and make complex model outputs interpretable to human operators. You'll partner with other science teams on researching new optimization techniques such as the Consensus Planning Protocol, and collaborate with Software Engineering to productionalize models on AWS infrastructure. This is a high-impact role where your work will directly influence delivery speed and cost to serve for every Amazon customer in North America. Key job responsibilities - Develop and maintain optimization models that generate volume plans for the North America fulfillment network, balancing constraints such as labor capacity, storage limits, transportation costs, and demand forecasts - Build Agentic AI and GenAI applications that make model outputs explainable and actionable for planners, translating complex optimization decisions into clear, human-interpretable insights - Design and implement Agentic AI-driven planning process automation to reduce manual intervention and accelerate planning cycles - Leverage Agentic AI to run network plan simulations, identify further optimization opportunities, and surface recommendations for improved network performance - Design and maintain metrics and frameworks to track, evaluate, and continuously improve optimal network performance - Partner with other science teams on researching new optimization / explainability techniques - Collaborate with the Software Engineering team to deploy and monitor models on AWS infrastructure - Conduct data analysis to identify improvement opportunities in supply chain planning processes, quantifying impact with data and anecdotes - Develop automated reporting and data pipelines to track model performance and planning outcomes across the network A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. 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: - Medical, Dental, and Vision Coverage - Maternity and Parental Leave Options - Paid Time Off (PTO) - 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 SCOT (Supply Chain Optimization Technologies) owns technologies that power Amazon's inventory and fulfillment decisions at global scale. Within SCOT, our team—Planning Optimization—owns the central coordination layer that determines optimal volume flow across the North America network, directly impacting delivery speed, cost to serve, and operational efficiency for hundreds of fulfillment sites. We use mathematical optimization, simulation, and Agentic AI/GenAI to continuously improve plan quality, automate planning workflows, and make model decisions explainable and trustworthy for business stakeholders.

The NASC & TOM Science team owns Operations Research, Machine Learning, and AI projects across the North America Sort Center (NASC) and Transportation Operations Management (TOM) planning and operations organizations. We turn complex network, labor, and capacity problems into deployed models that drive multi-million-dollar planning decisions every day. As a Data Scientist II, you will own the end-to-end Machine learning Operation cycle: Design, build, and ship machine learning and/or optimization models that directly shape Amazon's middle miles planning decisions. You will own end-to-end delivery — from problem framing with business partners, through modeling and validation, to deployment in internal model hosting platform and integration with downstream planning tools. You will work on problems such as: - Long- and short-horizon forecasting - Network and capacity optimization - GenAI / agentic systems - Defect prevention and adaptive planning You will partner closely with Engineering, Product, Engineering, and stakeholders to translate ambiguous operational pain points into measurable model outcomes. Key job responsibilities - Design and implement complex ML and optimization solutions (forecasting, MIP/LP, simulation, Deep learning / foundation model); - Drive end-to-end delivery of scalable models — from data exploration and feature engineering through training, evaluation, deployment, and post-launch monitoring; - Develop new modeling patterns and analytical frameworks for forecasting (multivariate, hierarchical, causal-DAG, model-chaining) and optimization; - Build robust model validation, backtesting, and monitoring pipelines; identify and eliminate sources of leakage, bias, and silent failure; - Define and own model performance metrics (e.g., WAPE) tied to business outcomes; - Partner with Data Engineering and Software Development to productionize models and define I/O contracts, packaging, and model CI/CD; - Excellent communication to present findings, tradeoffs, and recommendations clearly to stakeholders and senior leadership.

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. As a Senior Research Engineer embedded in our science team, you'll be instrumental in transforming innovative research into high-performance production systems. You'll collaborate directly with scientists to build and optimize large-scale transformer models for robotics applications. In this role, you'll balance deep technical optimization work with strategic input on model architecture decisions, ensuring our innovative robotics models are designed with performance in mind from the ground up. You'll leverage PyTorch and NVIDIA's acceleration stack and other compilation techniques to tackle ambitious performance targets, working at the intersection of large language models and real-world robotics applications. Key job responsibilities - Design, implement, and optimize distributed training systems that scale across thousands of GPUs and nodes for large-scale training workloads. - Develop high-performance optimizations to maximize throughput and efficiency. - Develop reusable frameworks and libraries to improve training reproducibility, reliability, and scalability for new model architectures. - Establish standards for reliability, maintainability, and security, ensuring systems are robust under rapid iteration. - Collaborate with researchers to influence model architectures for optimal hardware utilization - Develop comprehensive benchmarking frameworks to measure and optimize model performance A day in the life In this role, you will: - Optimize transformer blocks using custom CUDA kernels and TensorRT optimization techniques - Partner with scientists to analyze model architectures and propose efficiency improvements - Implement and benchmark various optimization strategies for large-scale models - Debug performance bottlenecks using NVIDIA profiling tools - Participate in technical discussions about new model architectures with the science team - Manage pre/post training runs and continue improve system stability and throughput - Prototype new acceleration approaches using emerging compilation frameworks

Have you ever ordered a product on Amazon and when that box with the smile arrived you wondered how it got to you so fast? Have you wondered where it came from and how much it cost Amazon to deliver it to you? We are looking for a Data Scientist who will be responsible to develop cutting-edge scientific solutions to optimize our fulfillment strategy across multiple regions of the world (EU, JP, IN and more), to maximize our Customer Experience and minimize our cost and carbon footprint. You will partner with the worldwide scientific community to help design the optimal fulfillment strategy for Amazon. You will also collaborate with technical teams to develop optimization tools for network flow planning and execution systems. Finally, you will also work with business and operational stakeholders to influence their strategy and gather inputs to solve problems. To be successful in the role, you will need deep analytical skills and a strong scientific background. The role also requires excellent communication skills, and an ability to influence across business functions at different levels. You will work in a fast-paced environment that requires you to be detail-oriented and comfortable in working with technical, business and technical teams. Key job responsibilities - Design and develop mathematical models to optimize inventory placement and product flows. - Design and develop statistical and optimization models for planning Supply Chain under uncertainty. - Manage several, high impact projects simultaneously. - Consult and collaborate with business and technical stakeholders across multiple teams to define new opportunities to optimize our Supply Chain. - Communicate data-driven insights and recommendations to diverse senior stakeholders through technical and/or business papers. - Leverage LLMs to improve explainability of our optimization solutions and drive engagement from supply chain planners across the world.

Are you passionate about helping customers achieve business transformation through AI? Do you want to lead forward-deployed teams that embed directly into the enterprise and unlock real business outcomes? And are you ready to operate as a general manager across engineering, science, and commercial strategy in the fastest-moving space in AI and infrastructure? The AWS Generative AI Innovation Center (GenAIIC) is on a mission to accelerate enterprise AI transformation across global customers going from beyond isolated use cases to holistic, C-suite-sponsored initiatives that reshape how organizations operate. We combine deep AI expertise across science, strategy, and business transformation. We start with the customer's most critical operational challenges and work backwards, and deploy multidisciplinary teams that embed with the customer, prove impact in 45-day sprints, and expand across the enterprise. We are a fast-moving, entrepreneurial team that values leaders who can operate across technical depth and commercial breadth. As the Head of AI Transformation, GenAIIC APJC Geo, you will own the end-to-end success of AI transformation engagements across the Asia Pacific, Japan, and Greater China region. You will lead a team of ML engineers, AI scientists, and AI strategists who work alongside customers to architect and deliver AI solutions that move and stay in production, realizing value. You will regularly engage with CFOs, CIOs, and C-suite executives — selling transformation, not technology. You must bring a GM mindset: equal fluency in engineering, applied science, go-to-market, and customer delivery. You are ready to roll up your sleeves alongside the team — whether that means scoping an agentic AI architecture, presenting to a board, or operationalizing a repeatable delivery motion across geos. You will partner with customers, AWS Sales, AWS service teams, AWS industry teams and AWS Professional Services delivery teams to meet the specific needs of the customer, and extend that use to other customers. Key job responsibilities Lead a high-performing, multidisciplinary team of ML engineers, AI scientists and strategists. Own the regional engagement pipeline — identify, qualify, and land C-suite-sponsored AI transformation programs with enterprise customers. Guide the team in designing, building, and deploying production AI solutions. Drive a land-and-expand motion: prove value in focused sprints, then scale across business units with executive sponsorship. Operate as a GM — balancing technical delivery, talent development, commercial outcomes, and operational excellence. Advise and influence customers on enterprise AI strategy, including architecture decisions, organizational readiness, and change management. Drive adoption of AWS generative AI services by delivering AI expertise and developing repeatable transformation playbooks. Develop new strategies and mechanisms to address evolving customer needs while increasing business velocity and impact for AWS. Influence product roadmap with service teams based on customer feedback. A day in the life Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

We are seeking a Robotics/AI Motor Control Scientist to develop cutting-edge machine learning algorithms for motor control systems in robots. In this role, you will focus on creating and optimizing intelligent motor control strategies to enable robots to perform complex, whole-body tasks. Your contributions will be essential in advancing robotics by enabling fluid, reliable, and safe interactions between robots and their environments. Key job responsibilities - Develop controllers that leverage reinforcement learning, imitation learning, or other advanced AI techniques to achieve natural, robust, and adaptive motor behaviors - Collaborate with multi-disciplinary teams to integrate motor control systems with robotic hardware, ensuring alignment with real-world constraints such as actuator dynamics and energy efficiency - Use simulation and real-world testing to refine and validate control algorithms - Stay updated on advancements in robotics, AI, and control systems to apply advanced techniques to robotic motion challenges - Lead technical projects from conception through production deployment - Mentor junior scientists and engineers - Bridge research initiatives with practical engineering implementation About the team Fauna Robotics, an Amazon company, is building capable, safe, and genuinely delightful robots for everyday life. Our goal is simple: make robots people actually want to live and interact with in everyday human spaces. We believe that future won’t arrive until building for robotics becomes far more accessible. Today, too much effort is spent reinventing the fundamentals. We’re changing that by developing tightly integrated hardware and software systems that make it faster, safer, and more intuitive to create real-world robotic products. Our work spans the full stack: mechanical design, control systems, dynamic modeling, and intelligent software. The focus is not just functionality, but experience. We’re building robots that feel responsive, expressive, and genuinely useful. At Fauna, you’ll work at the frontier of this space, helping define how robots move, manipulate, and interact with people in natural environments. It’s an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build. If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you. an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build. If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you.

As a Data Scientist on our team, you will leverage advanced analytics and machine learning to protect our cloud infrastructure from security threats. You'll develop and deploy sophisticated anomaly detection models, predictive algorithms, and real-time analysis systems that identify and help automate the mitigation of cyber threats across Amazon's infrastructure. Your expertise in statistical analysis, machine learning, and big data processing will be crucial in building scalable security solutions. You'll collaborate with software engineers, security engineers, and fellow data scientists to: - Analyze large-scale security data using statistical methods and data mining techniques - Create automated systems for real-time pattern recognition and risk assessment - Build data pipelines and ETL processes to handle massive security datasets - Translate complex analytical findings into actionable security insights We use the full power of AWS technologies, including Amazon SageMaker, EMR, and other ML/AI services to protect every AWS customer from security threats. Experience with Python and a strong background in statistical analysis and machine learning are essential. We're looking for a new teammate who is enthusiastic, empathetic, curious, motivated, reliable, and able to work effectively with a diverse team of peers. We want someone who will help us amplify the positive & inclusive team culture we've been building. We understand that life is dynamic and we have a flexible work environment that enables individuals to adjust their work schedule to accommodate personal needs. Our team is distributed, though most of the team is located in Maryland and Virginia. We generally keep core business hours of 10:00 AM EST - 3:00 PM EST, while allowing flexibility as needed. At AWS Security, it’s not about clocking hours, it’s about delivering results. On-Call Responsibility This position involves on-call responsibilities, typically for one week every two months. We don’t like getting paged in the middle of the night or on the weekend, so we work to ensure that our systems are fault tolerant. When we do get paged, we work together to resolve the root cause so that we don’t get paged for the same issue twice. Key job responsibilities - Running experiments to assess potential risk of security responses. - Expanding our existing LLM agent pipelines - Analyzing post mortems to understand what data signals could have prevented the occurence About the team Diverse Experiences Amazon Security 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 Amazon Security? At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & 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, training, 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

Are you passionate about solving complex business problems at scale through Generative AI? Do you want to build intelligent systems that reason, act, and learn from minimal supervision? Are you excited about taking innovative AI solutions from proof-of-concept to production? If so, we have an exciting opportunity for you on Amazon's Trustworthy Shopping Experience (TSE) team. At TSE, our vision is to guarantee customers a worry-free shopping experience by earning their trust that the products they buy are safe, authentic, and compliant with regulations and policy. We give customers confidence that Amazon stands behind every product and will make it right in the rare chance anything goes wrong. We do this in close partnership with our selling partners and empower them with best-in-class tools and expertise required to offer a high-quality selection of compliant products that customers trust. As an Applied Scientist, you will lead the development of next Gen AI solutions to automate complex manual investigation processes at Amazon scale. You will work on some of the most fascinating challenges in applied AI—building systems that reason and act autonomously, learn rich representations from structured and relational data without extensive labels, adapt rapidly from limited examples, improve through feedback and interaction, seamlessly connect visual and textual understanding, and compress complex model capabilities into efficient, deployable systems. Your innovations will deliver significant impact to cost-of-serving customers while maintaining the highest standards of trust and safety. This role offers end-to-end ownership—from initial research and proof-of-concept through production deployment. You will see your innovations serving hundreds of millions of customers within months, not years. Key job responsibilities • Design and build expertise deep agentic AI systems with multi-step reasoning, autonomous task execution, and multimodal intelligence with capabilities to handle feedback with long term as well as short term memory mechanisms. • Design and build expertise agentic AI systems with multi-step reasoning, autonomous task execution, and multimodal intelligence with capabilities to handle feedback with long term as well as short term memory mechanisms. • Productionize large scale models built on top of SFT (Supervised Finetuning) and RFT (Reinforced fine tuning) approaches (GRPO with RLVR, Process/Outcome Reward Models), few shot approaches (Contrastive, Prototypical) based on multimodal datasets • Enhance on existing Automatic prompt optimization techniques (GEPA & beyond) towards agentic optimization given the ground truth datasets to improve agentic planning. • Build novel production ready Finetuned transformer architectures (using LORA/Q-LORA/LLM-JEPA etc) and conventional supervised & unsupervised ML solutions to aid the multiple potential automation requirements • Identify customer and business problems at project level; invent or extend state-of-the-art approaches for complex LLM workflows involving unstructured text, documents, images, and relational data • Author or co-author research papers for peer-reviewed venues; serve as PC member at conferences when aligned with business needs • Prototype rapidly, iterate based on feedback, and deliver components at SDE 1+ level that integrate directly into production-scale systems • Engineer efficient systems balancing model capability, deployment cost, and resource usage; write significant code demonstrating technical excellence and maintainability • Scrutinize algorithm and software performance for improvements; resolve root causes leaving systems more maintainable • Contribute to tactical and strategic planning—team goals, priorities, and roadmaps—while providing architectural guidance for AI systems • Participate in engineering best practices with rigorous peer reviews; communicate design decisions clearly and participate in science reviews • Train new teammates & interns on component construction and integration; mentor less experienced scientists and participate in hiring processes About the team Investigation technology Product team in TSE is responsible for the human-in-the-loop products and technology used in the risk investigations at Amazon. The team is also responsible for reducing the cost of performing the investigations, by automating wherever possible and optimizing the experience where manual interventions are needed. The team leverages state-of-the art technology and GenAI to deliver the products and associated goals.