Careers

Do you want to be part of a team that's revolutionizing Amazon's fulfillment and packaging technology? Are you ready to optimize systems that process tens-of-millions of customer packages daily with the lowest cost to serve and a defect-free customer experience? Do you have a passion for solving complex science challenges and building a sustainable e-commerce experience? The Robotics Delivery and Packaging Innovation (RDPI) team is seeking an Applied Scientist who will join a team of experts in the field of Machine Learning (ML), Statistics, Operations Research, Computer Vision and Generative AI to work together to break new ground in the world of automated packaging solutions. The RDPI team owns mission-critical automation and packaging solutions that impact billions of customer shipments annually across Amazon’s WW marketplaces. We manage billions of dollars in material spend and packaging labor costs while driving significant reductions in carbon emissions. Our team is revolutionizing e-commerce through advanced packaging automation, innovative sortation technology, and sustainable solutions. We're dramatically reducing single-use plastics across our network while developing next-generation automated solutions that can handle the majority of our packaging needs. We're also transforming our supply chain through strategic investments in paper manufacturing and innovative materials, driving both substantial cost savings and environmental benefits. This is an exciting opportunity to work on large-scale automation challenges that directly impact customer experience, operational efficiency, and environmental sustainability at one of the world's largest e-commerce companies. You'll work in a collaborative environment where you can pursue ambitious 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 packaging experience of Amazon customers in the fulfillment technology space. If you are interested in robotics, computer vision, machine learning, operations research, statistics, big data, and building scalable solutions, this role is for you. Key job responsibilities A successful candidate in this role may perform some or all of the following responsibilities: - Leverage generative AI technologies to develop scalable solutions for automated product compatibility and safety assessments (e.g., evaluating product shipping compatibility, safety requirements, and packaging configurations) - Develop advanced AI models by extracting predictive features from multiple data sources (product/packaging images, product descriptions, sensor data, geospatial data) to forecast package-related damages and optimize packaging decisions based on customer preference prediction - Develop and implement computer vision solutions to automate packaging workflows and detect product/packaging defects in real-time operations - Build causal inference model to capture the downstream impacts of different packaging designs and delivery experience - Design and implement robotic control algorithms to optimize machine efficiency and meet diverse business objectives A day in the life Scientists on our team work daily with dedicated product and engineering partners to bring innovative solutions from concept to production. You'll divide your time between deep technical work—building models, analyzing results, iterating on algorithms—and collaborative activities like design reviews, stakeholder presentations, and cross-functional planning. You'll also have opportunities to support science initiatives across the broader RDPI organization (1500+ people), partnering with diverse teams to solve high-impact problems and scale your solutions across Amazon. About the team We are a team of scientists with diverse technical backgrounds spanning Machine Learning, Operations Research, Causal Inference, and Econometrics. We tackle complex, high-impact problems that directly influence Amazon's strategic decisions and financial performance. Our solutions typically require combining multiple methodologies, and you'll work collaboratively with other scientists while partnering closely with product and engineering teams to bring your innovations into production systems. You'll have the opportunity to grow your expertise across disciplines while delivering measurable business impact at scale.

Customer Experience and Business Trends (CXBT) is looking for an Applied Scientist to join their team. CXBT's mission is to create best-in-class AI agents that seamlessly integrate multimodal inputs like speech, images, and video, enabling natural, empathetic, and adaptive interactions. We leverage advanced architectures, cross-modal learning, interpretability, and responsible AI techniques to provide coherent, context-aware responses augmented by real-time knowledge retrieval. The ideal candidate will have expertise in Large Language Models (LLMs), speech, audio, Natural Language processing (NLP) or multimodal learning to pioneer innovations in data simulation, representation, generation, reasoning, retrieval, and evaluation. Key job responsibilities - Build scalable solutions for real-time conversational experiences, including multilingual support, customizable personalities, and conversational turn-taking. - Develop data simulation approaches that mimic real-world speech interactions. - Research and implement novel algorithms and modeling techniques. - Acquire and curate diverse datasets while ensuring user privacy. - Create robust evaluation metrics and test sets to assess language model performance. - Integrate human feedback to improve data selection and model performance. - Innovate in data representation and model training techniques. - Apply responsible AI practices throughout the development process. A day in the life Our team is dedicated to improving Amazon's products and services through evaluation of the end-to-end customer experience using both internal and external processes and technology. Our mission is to deeply understand our customers' experiences, challenge the status quo, and provide insights that drive innovation to improve that experience. Through our analysis and insights, we inform business decisions that directly impact customer experience as customers of new GenAI and LLM technologies. About the team Customer Experience and Business Trends (CXBT) is an organization made up of a diverse suite of functions dedicated to deeply understanding and improving customer experience, globally. We are a team of builders that develop products, services, ideas, and various ways of leveraging data to influence product and service offerings – for almost every business at Amazon – for every customer (e.g., consumers, developers, sellers/brands, employees, investors, streamers, gamers). Our approach is based on determining the customer need, along with problem solving, and we work backwards from there. We use technical and non-technical approaches and stay aware of industry and business trends. We are a global team, made up of a diverse set of profiles, skills, and backgrounds – including: Product Managers, Software Developers, Computer Vision experts, Solutions Architects, Data Scientists, Business Intelligence Engineers, Business Analysts, Risk Managers, and more.

Customer Experience and Business Trends (CXBT) is looking for an Applied Scientist to join their team. CXBT's mission is to create best-in-class AI agents that seamlessly integrate multimodal inputs like speech, images, and video, enabling natural, empathetic, and adaptive interactions. We leverage advanced architectures, cross-modal learning, interpretability, and responsible AI techniques to provide coherent, context-aware responses augmented by real-time knowledge retrieval. The ideal candidate will have expertise in Large Language Models (LLMs), speech, audio, Natural Language processing (NLP) or multimodal learning to pioneer innovations in data simulation, representation, generation, reasoning, retrieval, and evaluation. Key job responsibilities - Build scalable solutions for real-time conversational experiences, including multilingual support, customizable personalities, and conversational turn-taking. - Develop data simulation approaches that mimic real-world speech interactions. - Research and implement novel algorithms and modeling techniques. - Acquire and curate diverse datasets while ensuring user privacy. - Create robust evaluation metrics and test sets to assess language model performance. - Integrate human feedback to improve data selection and model performance. - Innovate in data representation and model training techniques. - Apply responsible AI practices throughout the development process. A day in the life Our team is dedicated to improving Amazon's products and services through evaluation of the end-to-end customer experience using both internal and external processes and technology. Our mission is to deeply understand our customers' experiences, challenge the status quo, and provide insights that drive innovation to improve that experience. Through our analysis and insights, we inform business decisions that directly impact customer experience as customers of new GenAI and LLM technologies. About the team Customer Experience and Business Trends (CXBT) is an organization made up of a diverse suite of functions dedicated to deeply understanding and improving customer experience, globally. We are a team of builders that develop products, services, ideas, and various ways of leveraging data to influence product and service offerings – for almost every business at Amazon – for every customer (e.g., consumers, developers, sellers/brands, employees, investors, streamers, gamers). Our approach is based on determining the customer need, along with problem solving, and we work backwards from there. We use technical and non-technical approaches and stay aware of industry and business trends. We are a global team, made up of a diverse set of profiles, skills, and backgrounds – including: Product Managers, Software Developers, Computer Vision experts, Solutions Architects, Data Scientists, Business Intelligence Engineers, Business Analysts, Risk Managers, and more.

Are you passionate about leading teams that apply formal verification, program analysis, constraint-solving, and theorem proving to solve critical customer problems at scale? Do you want to build and grow organizations that create products customers love? If so, then we have an exciting opportunity for you. In this role, you will define the technical vision and science agenda for your organization, working across AWS to identify high-impact opportunities where automated reasoning can transform customer experiences. You will build, mentor, and grow a team of world-class applied scientists and engineers, establishing your organization as a center of excellence in formal methods. You will represent AWS to the academic community, industry partners, and customers, shaping the future direction of automated reasoning in cloud computing. Key job responsibilities Define and drive the science agenda for your organization, identifying ambiguous problem spaces where formal methods can deliver transformational customer value Establish technical vision across multiple product areas, ensuring alignment with AWS-wide security, safety, and correctness initiatives Present and defend organization-wide technical decisions to senior leadership and represent AWS at premier academic conferences and industry forums Serve as functional thought leader for automated reasoning across AWS, sought after for strategic technical decisions by VP-level stakeholders Build partnerships with academic institutions and industry leaders to advance the state of the art in formal verification and program analysis Recruit, develop, and retain world-class talent in formal verification, program analysis, and GenAI Mentor and grow applied scientists from mid-level to principal level, with demonstrated track record of developing technical leaders Own end-to-end delivery of multiple customer-facing products leveraging formal methods, AI, and ML. Drive products from research prototype to production systems serving millions of customers Establish metrics and mechanisms to measure customer impact and business value of science initiatives Scale solutions to meet rapidly growing customer demand while maintaining scientific rigor Partner with product and engineering leaders to translate customer needs into research directions

Sponsored Products and Brands (SPB) is at the heart of Amazon Advertising, helping millions of advertisers—from small businesses to global brands—connect with customers at the moments that matter most. Our advertising solutions enable sellers, vendors, and brand owners to grow their businesses by reaching shoppers with relevant, engaging ads across Amazon's store and beyond. We're obsessed with delivering measurable results for advertisers while creating a delightful shopping experience for customers. Are you interested in defining the science behind the future of advertising? Sponsored Products and Brands science teams are pioneering breakthrough agentic AI systems—pushing the boundaries of large language models, autonomous reasoning, planning, and decision-making to build intelligent agents that fundamentally transform how advertisers succeed on Amazon. As an SPB applied science leader, you'll have end-to-end ownership of the product and scientific vision, research agenda, model architectures, and evaluation frameworks required to deliver state-of-the-art agentic AI solutions for our advertising customers. You'll get to work on problems that are fast-paced, scientifically rich, and deeply consequential. You'll also be able to explore novel research directions, take bold bets, and collaborate with remarkable scientists, engineers, and product leaders. We'll look for you to bring your diverse perspectives, deep technical expertise, and scientific rigor to make Amazon Advertising even better for our advertisers and customers. With global opportunities for talented scientists and science leaders, you can decide where a career in Amazon Ads Science takes you! We are kicking off a new initiative within SPB to leverage agentic AI solutions to revolutionize how advertisers create, manage, and optimize their advertising campaigns. This is a unique opportunity to lead a business-critical applied science initiative from its inception—defining the scientific charter, establishing foundational research pillars, and building a multi-year science roadmap for transformative impact. As the single-threaded applied science leader, you will build and guide a dedicated team of applied scientists, research scientists, and machine learning engineers, working closely with cross-functional engineering and product partners, to research, develop, and deploy agentic AI systems that fundamentally reimagine the advertiser journey. Your charter will begin with advancing the science behind intelligent agents that simplify campaign creation, automate optimization decisions through autonomous reasoning and planning, and deliver personalized advertising strategies at scale. You will pioneer novel approaches in areas such as LLM-based agent architectures, multi-step planning and tool use, retrieval-augmented generation, reinforcement learning from human and business feedback, and robust evaluation methodologies for agentic systems. You will expand to proactively identify and tackle the next generation of AI-powered advertising experiences across the entire SPB portfolio. This high-visibility role places you as the science leader driving our strategy to democratize advertising success—making it effortless for advertisers of all sizes to achieve their business goals while delivering relevant experiences for Amazon customers. Key job responsibilities Build, mentor, and lead a new, high-performing applied science organization of applied scientists, research scientists, and engineers, fostering a culture of scientific excellence, innovation, customer obsession, and ownership. Define, own, and drive the long-term scientific and product vision and research strategy for agentic AI-powered advertising experiences across Sponsored Products and Brands—identifying the highest-impact research problems and charting a path from exploration to production. Lead the research, design, and development of novel agentic AI models and systems—including LLM-based agent architectures, multi-agent orchestration, planning and reasoning frameworks, tool-use mechanisms, and retrieval-augmented generation pipelines—that deliver measurable value for advertisers and create delightful, intuitive experiences. Establish rigorous scientific methodology and evaluation frameworks for assessing agent performance, reliability, safety, and advertiser outcomes, setting a high bar for experimentation, reproducibility, and offline-to-online consistency. Partner closely with senior business, engineering, and product leaders across Amazon Advertising to translate advertiser pain points and business opportunities into well-defined science problems, and deliver cohesive, production-ready solutions that drive advertiser success. Drive execution from research to production at scale, ensuring models and agentic systems meet high standards for quality, robustness, latency, safety, and reliability for mission-critical advertising services operating at Amazon scale. Champion a culture of scientific inquiry and technical depth that encourages bold experimentation, publication of novel research, relentless simplification, and continuous improvement. Communicate your team's scientific vision, research breakthroughs, strategy, and progress to senior leadership and key stakeholders, ensuring alignment with broader Amazon Advertising objectives and contributing to Amazon's position at the forefront of applied AI. Develop a science roadmap directly tied to advertiser outcomes, revenue growth, and business plans, delivering on commitments for high-impact research and modeling initiatives that shape the future of AI-powered digital advertising.

Amazon Industrial Robotics is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models. We leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence. We are pioneering the development of robotics foundation models that: - Enable unprecedented generalization across diverse tasks - Integrate multi-modal learning capabilities (visual, tactile, linguistic) - Accelerate skill acquisition through demonstration learning - Enhance robotic perception and environmental understanding - Streamline development processes through reusable capabilities The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment. Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration. As an Applied Scientist, you will develop and improve machine learning systems that help robots perceive, reason, and act in real-world environments. You will leverage state-of-the-art models (open source and internal research), evaluate them on representative tasks, and adapt/optimize them to meet robustness, safety, and performance needs. You will invent new algorithms where gaps exist. You’ll collaborate closely with research, controls, hardware, and product-facing teams, and your outputs will be used by downstream teams to further customize and deploy on specific robot embodiments. Key job responsibilities - Leverage state-of-the-art models for targeted tasks, environments, and robot embodiments through fine-tuning and optimization. - Execute rapid, rigorous experimentation with reproducible results and solid engineering practices, closing the gap between sim and real environments. - Build and run capability evaluations/benchmarks to clearly profile performance, generalization, and failure modes. - Contribute to the data and training workflow: collection/curation, dataset quality/provenance, and repeatable training recipes. - Write clean, maintainable, well commented and documented code, contribute to training infrastructure, create tools for model evaluation and testing, and implement necessary APIs - Stay current with latest developments in foundation models and robotics, assist in literature reviews and research documentation, prepare technical reports and presentations, and contribute to research discussions and brainstorming sessions. - Work closely with senior scientists, engineers, and leaders across multiple teams, participate in knowledge sharing, support integration efforts with robotics hardware teams, and help document best practices and methodologies.

Advertising at Amazon is growing incredibly fast and we are responsible for defining and delivering a collection of advertising products that drive discovery and sales. Amazon Business Ads is equally growing fast ($XXXMs to $XBs) and owns engineering and science for the AB WW ad experience. We build business-to-business (“B2B”) specific ad solutions distributed across retail and ad systems for shopper and advertiser experiences. Some include new ad placements or widgets, creatives, sourcing techniques, ad campaign management capabilities and much more! We consider unique AB qualities which are differentiated from the consumer experience such as varying shopper role types, purchasing complexities based on business size and industry (eg education vs healthcare), AB specific features (eg business discounts, buying policies to restrict and prefer products), and AB buyer behaviors (eg buying in bulk). We are seeking a scientific leader who can drive innovation in complex problem areas and new business initiatives. The ideal candidate will: Technical & Research Requirements: * Demonstrate fluency in Python, R, Matlab or other statistical languages and familiarity with deep learning frameworks like PyTorch, TensorFlow * Lead end-to-end solution development from research to prototyping and experimentation * Write and deploy significant parts of scientifically novel software solutions into production Leadership & Influence: * Drive team's scientific agenda by proposing new initiatives and securing management buy-in including PM, SDM * Mentor colleagues and contribute to their professional development * Build consensus on large projects and influence decisions across different teams in Ads Key Leadership Principles: * Dive Deep: Uncover non-obvious insights in data * Deliver Results: Create solutions aligned with customer and product needs * Learn and Be Curious: Demonstrate self-driven desire to explore new research areas * Earn Trust: Build relationships with stakeholders through understanding business needs

Amazon is looking for a motivated individual with strong statistical, analytical skills and technological experience to join the DIGI (Data Infrastructure and Generative Intelligence) Ad Sales Finance analytics team. In this position the successful candidate will be responsible for partnering with Finance and Business leaders to optimize Sales Forecasts Key job responsibilities - Build and train models to support forecasting and planning for Advertising Sales Finance - Have strong technical experience, but also be able to work with non-tech partners and communicate complex and technical topics in a simple and understandable fashion - Have a good understanding of machine learning or statistical modeling techniques, including a strong understanding of model parameters and how they affect performance - Understand time-series forecasting techniques (e.g., STL decomposition, ETS/Holt-Winters, ARIMA, Prophet, or similar models) - Familiarity with hierarchical or segmented forecasting problems (e.g., product, region, channel, or customer-level splits) - Apply theoretical or statistical models in an applied, real-world environment - Perform model evaluation such as confidence intervals, error metrics, backtesting, and validation datasets - Work with large, complex datasets across multiple dimensions - Translate analytical findings into clear, actionable insights for business stakeholders A day in the life In this position the successful candidate will be responsible for partnering with Finance and Business leaders to expand and optimize forecasting models that supports weekly, monthly, quarterly and annual reviews for the Display Ads Finance group and our stakeholders. About the team The Advertising Sales Finance Analytics & FP&A team's responsibilities comprise of corporate reporting, planning, Headcount & OpEx, Goals reporting, and ad-hoc analysis. We support Advertising leaders and finance teams by coordinating and consolidating deliverables, centralizing and standardizing processes, establishing financial controls and mechanisms, building tools that improve the speed of decision making, and providing insightful financial analysis on the short and long term strategy of Advertising.

We are seeking a talented, customer-focused applied scientist to join our JCI Measurement and Optimization Science Team (JCI MOST), with a charter to build scalable systems that automatically detect pricing defects, implement intelligent corrections, measure intervention impacts, and deliver data-driven pricing strategies to leadership. This role requires an individual with exceptional machine learning, LLM, and Causal Inference expertise, strong system architecture capabilities, excellent cross-functional collaboration skills, business acumen, and an entrepreneurial spirit to drive measurable improvements in pricing quality and competitiveness. We are looking for an experienced innovator who is a self-starter, comfortable with ambiguity, demonstrates strong attention to detail, and thrives in a fast-paced, data-driven environment. Key job responsibilities Key Job Responsibilities • Build scalable defect detection systems that automatically identify pricing anomalies, competitive gaps, and quality issues across millions of products using ML and LLM models and real-time monitoring • Deploy automated defect remediation with intelligent pricing recommendations, and validation frameworks that reduce manual intervention requirements • Measure impact and drive strategy by establishing robust measurement frameworks, designing large-scale experiments, building attribution models, and developing executive dashboards that translate findings into actionable insights for leadership • Lead cross-functional collaboration by partnering with product, engineering, and science teams to deploy solutions at scale while communicating complex technical concepts clearly to executive audiences • Stay at the forefront of innovation by applying state-of-the-art techniques in ML, deep learning, LLM, and causal inference to pricing quality challenges while fostering rapid experimentation and continuous learning

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 extreme. We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers. No industries or subject areas are out of bounds. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We are constantly learning through programs that are local, regional, and global. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Our team highly values work-life balance, mentorship and career growth. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We care about your career growth and strive to assign projects and offer training that will challenge you to become your best.