Careers

Are you interested in shaping the future of Advertising and B2B Sales? We are a growing science and engineering team with an exciting charter and need your passion, innovative thinking, and creativity to help take our products to new heights. Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products are strategically important to our businesses driving long term growth. We break fresh ground in product and technical innovations every day! Within the Advertising Sales organization, we are building a central AI/ML team and are seeking top science talent to build new, science-backed services to drive success for our customers. Our goal is to transform the way account teams operate by creating actionable insights and recommendations they can share with their advertising accounts, and ingesting Generative AI throughout their end-to-end workflows to improve their work efficiency. As a part of our team, you will bring deep expertise in Generative AI and quantitative modeling (forecasting, recommender systems, reinforcement learning, causal inferencing or generative artificial intelligence) to build and refine models that can be implemented in production. You will contribute to chart new courses with our ad sales support technologies, and you have the communication skills necessary to explain complex technical approaches to a variety of stakeholders and customers. You will be part of a team of fellow scientists and engineers taking on iterative approaches to tackle big, long-term problems. Why you will love this opportunity: Amazon has invested heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon's Retail and Marketplace businesses. We deliver billions of ads impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit with a broad mandate to experiment and innovate. Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences; this is your opportunity to work within the fastest growing businesses across all of Amazon! Define a long-term scientific vision for our advertising sales business, driven from our customers' needs, translating that direction into specific plans for scientists, engineers and product teams. This role combines scientific leadership, organizational ability, technical strength, product focus, and business understanding. Key job responsibilities - Conceptualize and lead state-of-the-art research on new Machine Learning and Generative Artificial Intelligence solutions to optimize all aspects of the Ad Sales business - Guide the technical approach for the design and implementation of successful models and algorithms in support of expert cross-functional teams delivering on demanding projects - Conduct deep data analysis to derive insights to the business, and identify gaps and new opportunities - Run regular A/B experiments, gather data, and perform statistical analysis - Work closely with software engineers to deliver end-to-end solutions into production - Improve the scalability, efficiency and automation of large-scale data analytics, model training, deployment and serving About the team Sales AI is a central science and engineering organization within Amazon Advertising Sales that powers selling motions and account team workflows via state-of-the-art of AI/ML services. Sales AI is investing in a range of sales intelligence models, including the development of advertiser insights, recommendations and Generative AI-powered applications throughout account team workflows.

Have you ever wondered what it takes to transform millions of manual network planning decisions into AI-powered precision? Network Planning Solutions is looking for scientific innovators obsessed with building the AI/ML intelligence that makes orchestrating complex global operations feel effortless. Here, you'll do more than just build models; you'll create 'delight' by discovering and deploying the science that delivers exactly what our customers need, right when they need it. If you're ready to transform complex data patterns into breakthrough AI capabilities that power intuitive human experiences, you've found your team. Network Planning Solutions architects and orchestrates Amazon's customer service network of the future. By building AI-native solutions that continuously learn, predict and optimize, we deliver seamless customer experiences and empower associates with high-value work—driving measurable business impact at a global scale. As a Sr. Manager, Applied Science, you will own the scientific innovation and research initiatives that make this vision possible. You will lead a team of applied scientists and collaborate with cross-functional partners to develop and implement breakthrough scientific solutions that redefine our global network. Key job responsibilities Lead AI/ML Innovation for Network Planning Solutions: - Develop and deploy production-ready demand forecasting algorithms that continuously sense and predict customer demand using real-time signals - Build network optimization algorithms that automatically adjust staffing as conditions evolve across the service network - Architect scalable AI/ML infrastructure supporting automated forecasting and network optimization capabilities across the system Drive Scientific Excellence: - Build and mentor a team of applied scientists to deliver breakthrough AI/ML solutions - Design rigorous experiments to validate hypotheses and quantify business impact - Establish scientific excellence mechanisms including evaluation metrics and peer review processes Enable Strategic Transformation: - Drive scientific innovation from research to production - Design and validate next-generation AI-native models while ensuring robust performance, explainability, and seamless integration with existing systems. - Partner with Engineering, Product, and Operations teams to translate AI/ML capabilities into measurable business outcomes - Navigate ambiguity through experimentation while balancing innovation with operational constraints - Influence senior leadership through scientific rigor, translating complex algorithms into clear business value A day in the life Your day will be a dynamic blend of scientific innovation and strategic problem-solving. You'll collaborate with cross-functional teams, design AI algorithms, and translate complex data patterns into intuitive solutions that drive meaningful business impact. About the team We are Network Planning Solutions, a team of scientific innovators dedicated to reshaping how global service networks operate. Our mission is to create AI-native solutions that continuously learn, predict, and optimize customer experiences. We empower our associates to tackle high-value challenges and drive transformative change at a global scale.

The Amazon Fulfillment Technologies (AFT) Science team is seeking an exceptional Applied Scientist with strong operations research and optimization expertise to develop production solutions for one of the most complex systems in the world: Amazon's Fulfillment Network. At AFT Science, we design, build, and deploy optimization, statistics, machine learning, and GenAI/LLM solutions that power production systems running across Amazon Fulfillment Centers worldwide. We tackle a wide range of challenges throughout the network, including labor planning and staffing, pick scheduling, stow guidance, and capacity risk management. Our mission is to develop innovative, scalable, and reliable science-driven production solutions that exceed the published state of the art, enabling systems to run optimally and continuously (from every few minutes to every few hours) across our large-scale network. Key job responsibilities As an Applied Scientist, you will collaborate with scientists, software engineers, product managers, and operations leaders to develop optimization-driven solutions that directly impact process efficiency and associate experience in the fulfillment network. Your key responsibilities include: - Develop deep understanding and domain knowledge of operational processes, system architecture, and business requirements - Dive deep into data and code to identify opportunities for continuous improvement and disruptive new approaches - Design and develop scalable mathematical models for production systems to derive optimal or near-optimal solutions for existing and emerging challenges - Create prototypes and simulations for agile experimentation of proposed solutions - Advocate for technical solutions with business stakeholders, engineering teams, and senior leadership - Partner with software engineers to integrate prototypes into production systems - Design and execute experiments to test new or incremental solutions launched in production - Build and monitor metrics to track solution performance and business impact About the team Amazon Fulfillment Technology (AFT) designs, develops, and operates end-to-end fulfillment technology solutions for all Amazon Fulfillment Centers (FCs). We harmonize the physical and virtual worlds so Amazon customers can get what they want, when they want it. The AFT Science team brings expertise in operations research, optimization, statistics, machine learning, and GenAI/LLM, combined with deep domain knowledge of operational processes within FCs and their unique challenges. We prioritize advancements that support AFT tech teams and focus areas rather than specific fields of research or individual business partners. We influence each stage of innovation from inception to deployment, which includes both developing novel solutions and improving existing approaches. Our production systems rely on a diverse set of technologies, and our teams invest in multiple specialties as the needs of each focus area evolve.

This position requires that the candidate selected be a US Citizen and must currently possess and maintain an active TS/SCI security clearance with polygraph. The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Data Scientist to join our team at Amazon Web Services (AWS). Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? In this role, you'll work directly with customers to design, evangelize, implement, and scale AI/ML solutions that meet their technical requirements and business objectives. You'll be a key player in driving customer success through their AI transformation journey, providing deep expertise in data science, machine learning, generative AI, and best practices throughout the project lifecycle. As a Data Scientist within the AWS Professional Services organization, you will be proficient in architecting complex, scalable, and secure machine learning solutions tailored to meet the specific needs of each customer. You'll help customers imagine and scope the use cases that will create the greatest value for their businesses, develop statistical models and analytical frameworks, select and train the right models, and define paths to navigate technical or business challenges. Working closely with stakeholders, you'll assess current data infrastructure, perform exploratory data analysis, develop proof-of-concepts, and propose effective strategies for implementing AI and generative AI solutions at scale. You will design and run experiments, research new algorithms, extract insights from complex datasets, and find new ways of optimizing risk, profitability, and customer experience. The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides assistance through a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver focused guidance through our global specialty practices, which cover a variety of solutions, technologies, and industries. Key job responsibilities - Designing and implementing complex, scalable, and secure AI/ML solutions on AWS tailored to customer needs, including developing statistical models, performing feature engineering, and selecting appropriate algorithms for specific use cases - Developing and deploying machine learning models and generative AI applications that solve real-world business problems, conducting experiments, performing rigorous statistical analysis, and optimizing for performance at scale - Collaborating with customer stakeholders to identify high-value AI/ML use cases, gather requirements, analyze data quality and availability, and propose effective strategies for implementing machine learning and generative AI solutions - Providing technical guidance on applying AI, machine learning, and generative AI responsibly and cost-efficiently, performing model validation and interpretation, troubleshooting throughout project delivery, and ensuring adherence to best practices - Acting as a trusted advisor to customers on the latest advancements in AI/ML, emerging technologies, statistical methodologies, and innovative approaches to leveraging diverse data sources for maximum business impact - Sharing knowledge within the organization through mentoring, training, creating reusable AI/ML artifacts and analytical frameworks, and working with team members to prototype new technologies and evaluate technical feasibility

The Stores Economics and Science (SEAS) team is an interdisciplinary science and economics team whose mission is to solve high-risk, high-return problems for the Stores organization. We leverage frontier science, partner with teams across Amazon, and learn from the tools, experience, and perspectives of others. Our work spans rapid responses to pressing leadership questions, collaborative partnerships to help other teams achieve their goals, and multi-year scientific bets with large upside potential. We are looking for an economist who can use data-driven modeling and analyses to make the right trade-offs and solve impactful business problems. We seek creative thinkers who can combine a strong economic toolbox with a desire to learn from others, and who know how to execute and deliver on big ideas. In this role, you will contribute to SEAS' mission in two key ways. First, you will leverage your economic expertise to help design and validate scientific solutions for pressing business challenges. This will involve applying advanced analytical techniques, conducting rigorous data analysis, and proactively proposing high-impact initiatives that can be rapidly prototyped and scaled. Secondly, you will play a crucial role in translating complex economic models and insights into actionable recommendations that directly inform leadership decisions across the organization. This will require strong communication skills to effectively collaborate with cross-functional partners and drive meaningful change. Key job responsibilities - Collaborate with cross-functional partner teams to understand their challenges and translate them into rigorous economic frameworks that can be addressed through data analysis, modeling, and experimentation. - Own the end-to-end development of economic models and analyses, including conducting necessary data gathering, analysis, and validation to drive actionable insights, and - Effectively communicate your economic findings, models, and proposed solutions to senior business stakeholders, incorporating their feedback to refine your work.

Are you passionate about applying machine learning and data-driven techniques to solve real-world problems at global scale? Amazon is seeking an Applied Scientist who combines curiosity, creativity, and strong analytical skills to build models and algorithms that power customer experiences and business decisions. As an Applied Scientist II, you will work with senior scientists and engineers to design, train, and deploy ML models using large-scale datasets. You will experiment with modern techniques in supervised and unsupervised learning, natural language processing, computer vision, or optimization—depending on the team’s focus area. You’ll also have opportunities to learn Amazon’s scalable infrastructure, experiment platforms, and science best practices. This role is ideal for someone early in their career who enjoys working in collaborative, multidisciplinary teams and is excited by the opportunity to learn, innovate, and deliver measurable impact to customers. Key job responsibilities 1.Collaborate with scientists, engineers, and product managers to define and frame business problems as ML or optimization tasks. 2.Build, train, and evaluate models using large, complex datasets. 3.Implement scalable data pipelines and model-serving systems. 4.Analyze experimental results, draw insights, and refine models to improve accuracy and robustness. 5.Communicate findings and recommendations to technical and non-technical audiences. 6.Continuously learn and apply new algorithms and techniques to improve existing systems.

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.

As part of the AWS Applied AI Solutions organization, we have a mission to build delightful AI solutions that improve human capabilities and business outcomes. We will accomplish this by accelerating our customers' businesses through delivery of intuitive and differentiated AI solutions that solve enduring business challenges. We blend vision with curiosity and Amazon's real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use. The Applied Scientist will contribute to the development of Agentic AI solutions leveraging Gen AI. The role requires extending existing scientific techniques and inventing new ones to address specific customer needs. You should be comfortable working semi-autonomously on difficult problems with visible risks or roadblocks. You'll work closely with technical leaders within the team. We're looking for scientists who can maintain high standards while moving quickly, prioritizing both rapid experimentation and responsible AI development to deliver measurable customer impact. Key job responsibilities * Design and implement solutions that extend or adapt scientific approaches for customer needs * Deliver components into production that meet high quality standards (efficient, reproducible, testable code) * Produce science outputs demonstrating correctness, scholarship, and scientific rigor * Work with product, engineering, and science teams to deliver impactful AI features * Contribute to operational excellence in the team's deliverables About the team AWS Solutions As part of the AWS solutions organization, we have a vision to provide business applications, leveraging Amazon's unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers' businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon's real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use.

This position requires that the candidate selected be a US Citizen and must currently possess and maintain an active TS/SCI security clearance with polygraph. The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Machine Learning Engineer to join our team at Amazon Web Services (AWS). Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? In this role, you'll work directly with customers to design, evangelize, implement, and scale AI/ML solutions that meet their technical requirements and business objectives. You'll be a key player in driving customer success through their AI transformation journey, providing deep expertise in machine learning, generative AI, and best practices throughout the project lifecycle. As a Machine Learning Engineer within the AWS Professional Services organization, you will be proficient in architecting complex, scalable, and secure machine learning solutions tailored to meet the specific needs of each customer. You'll help customers imagine and scope the use cases that will create the greatest value for their businesses, select and train and fine tune the right models, and define paths to navigate technical or business challenges. Working closely with stakeholders, you'll assess current data infrastructure, develop proof-of-concepts, and propose effective strategies for implementing AI and generative AI solutions at scale. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides assistance through a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver focused guidance through our global specialty practices, which cover a variety of solutions, technologies, and industries. Key job responsibilities - Designing and implementing complex, scalable, and secure AI/ML solutions on AWS tailored to customer needs, including selecting and fine-tuning appropriate models for specific use cases - Developing and deploying machine learning models and generative AI applications that solve real-world business problems, conducting experiments and optimizing for performance at scale - Collaborating with customer stakeholders to identify high-value AI/ML use cases, gather requirements, and propose effective strategies for implementing machine learning and generative AI solutions - Providing technical guidance on applying AI, machine learning, and generative AI responsibly and cost-efficiently, troubleshooting throughout project delivery and ensuring adherence to best practices - Acting as a trusted advisor to customers on the latest advancements in AI/ML, emerging technologies, and innovative approaches to leveraging diverse data sources for maximum business impact - Sharing knowledge within the organization through mentoring, training, creating reusable AI/ML artifacts, and working with team members to prototype new technologies and evaluate technical feasibility About the team 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. 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. 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. 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.

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.