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 deliver billions of ad impressions and millions of clicks and 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 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 be a thought leader as we 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. As a senior lead, you will have the excitement to take 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.

As a Senior Applied Scientist on our Agentic AI Professional Services Experience team, you will be instrumental in advancing the frontier of human-agent collaboration for enterprise solutions. You will leverage your deep expertise in machine learning and artificial intelligence to develop intelligent systems that enhance how professionals interact with agentic AI tools, driving innovation in professional services delivery while balancing user experience, ethics, and business outcomes. In this role, you will shape the future of professional services by creating AI agents that augment human capabilities, streamline complex workflows, and deliver unprecedented value to customers. Your work will define how the next generation of professionals collaborate with intelligent systems, establishing new paradigms for productivity, creativity, and problem-solving in enterprise environments. Key job responsibilities - Architect and design AI agent systems that can effectively understand, reason about, and execute professional services workflows - Perform hands-on analysis and modeling of enormous data sets to develop insights that increase service effectiveness and business outcomes, while maintaining exceptional customer experience - Drive end-to-end Machine Learning projects involving agentic AI that navigate high degrees of ambiguity, scale, and complexity - Design and implement advanced machine learning models for agent decision-making, natural language understanding, and contextual reasoning - Conduct proof-of-concept development, experimentation, optimization, and production deployment of AI agent systems - Collaborate closely with software engineers to productionize ML models for agentic AI solutions - Design, execute, and analyze A/B experiments to evaluate agent performance, user satisfaction, and business impact - Establish scalable, efficient, automated processes for large-scale data analysis, agent behavior modeling, model validation, and serving - Research and implement new approaches for agent learning, reasoning, and interaction with human professionals - Develop frameworks for evaluating agent effectiveness, safety, and alignment with human objectives About the team ABOUT AWS: 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. 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.

Amazon AI is looking for world class scientists and engineers to join its AWS AI. This group is entrusted with developing core natural language processing, generative AI, deep learning, automated reasoning, and machine learning algorithms for AWS. You will invent, implement, and deploy state-of-the-art machine learning and automated reasoning algorithms and systems. You will build prototypes and explore conceptually new solutions. You will deliver innovative and impactful features into production. You will interact closely with our customers and with the academic community. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. 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. About the team The Amazon Web Services (AWS) agentic AI team uses generative AI and foundation models to reimagine the experience of all builders on AWS. From the IDE to web-based tools and services, AI will help engineers work on large and small applications. We explore new technologies and find creative solutions. Curiosity and an explorative mindset can find a place here to impact the life of engineers around the world. If you are excited about this space and want to enlighten your peers with new capabilities, this is the team for you.

Amazon.com strives to be Earth's most customer-centric company where people can find and discover anything they want to buy online. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Are you seeking an environment where you can drive innovation? Do you want to apply learning techniques and advanced mathematical modeling to solve real world problems? Do you want to play a key role in the future of Amazon's Retail business? This job for you! The Customer Behavior Analytics (CBA) team at Amazon is responsible for the architecture, design, implementation of tools used to understand customer behavior and value generation for all Amazon programs. Come and join us! Amazon’s CBA team is looking for ML Scientists, who can work at the intersection of economics, statistics and machine learning; and leverage the power of big data to solve complex problems like long-term causal effect estimation.

Over the past 20 years, Amazon has reinvented on behalf of the consumer and has become one of the largest internet retailers in the world. Amazon is now reinventing on behalf of the business customer and is building the most innovative Business-to-Business (B2B) online store in the world. At Amazon Business, we set out every day to innovate and disrupt the status quo. We stand at the intersection of tech and retail in the B2B space developing innovative purchasing and procurement solutions to help businesses and organizations reimagine buying. Bring your insight, imagination and a healthy disregard for the impossible. Join us in building and celebrating the value of Amazon Business to buyers and sellers of all sizes, unlocking our potential worldwide. The Analytics Data Product & Tech (ADAPTech) team is a strategic partner to the WW Sales organization, playing a key role in driving sales productivity through three primary workstreams. First, the Analytics team provides data-driven insights and reporting tools to measure business, customer, and employee performance. Second, the Products and Science team develops transformative tools that help Account Executives (AEs) to prioritize accounts, recommend product features, and engage more effectively with customers. Finally, the Data Management and Governance teams ensure AEs have access to accurate and enriched customer information across our tools. We're seeking an Applied Scientist to join our team to improve the productivity and efficiency of AEs. You'll be part of expanding GenAI capabilities and scaling its impact across global markets. A successful Applied Scientist at Amazon demonstrates bias for action and operates in a startup environment, with leadership skills, and proven ability to build and manage medium-scale modeling projects, identify data requirements, build methodology and tools that are statistically grounded. We need great leaders to think big and design new solutions to solve complex problems using machine learning (ML) and Generative AI techniques to improve our customers’ experience when using AB. You have hands-on experience making the right decisions about technology, models and methodology choices. Key job responsibilities As an Applied Scientist, you will primarily leverage machine learning techniques and generative AI to outreach customers based on their life cycle stage, behavioral patterns, and purchase history. You may also perform text mining and insight analysis of real-time customer conversations and make the model learn and recommend the solutions. Your work will directly impact the trust customers place in Amazon Business. You will partner with product management and technical leadership to identify opportunities to innovate customer journey experiences. You will identify new areas of investment and work to align product roadmaps to deliver on these opportunities. As a science leader, you will not only develop unique scientific solutions, but also play a crucial role in shaping strategies. Additional responsibilities include: -Design, implement, test, deploy and maintain innovative data and machine learning solutions to further the customer experience. -Create experiments and prototype implementations of new learning algorithms and prediction techniques -Develop algorithms for new capabilities and trace decisions in the data and assess how proposed changes could potentially impact business metrics to cater needs of Amazon Business Sales -Build models that measure incremental value, predict growth, define and conduct experiments to optimize engagement of AB customers, and communicate insights and recommendations to product, sales, and finance partners. A day in the life In this role, you will be a technical expert with significant scope and impact. You will work with Technical Product Managers, Data Engineers, other Scientists, and Salesforce developers, to build new and enhance existing ML models to optimize customer experience. You will prototype and test new ideas, iterate quickly, and deploy models to production. Also, you will conduct in-depth data analysis and feature engineering to build robust ML models.

The Mission of Amazon's Artificial General Intelligence (AGI) team is to "Build world-class general-purpose intelligence services that benefits every Amazon business and humanity." Are you a data enthusiast? Are you a creative big thinker who is passionate about using data to direct decision making and solve complex and large-scale challenges? If so, then this position is for you! We are looking for a motivated individual with strong analytical and communication skills to join us. In this role, you will apply advanced analytics techniques, AI/ML, and statistical concepts to derive insights from massive datasets. The ideal candidate should have expertise in AI/ML, statistical analysis, and the ability to write code for building models and pipelines to automate data and analytics processing. They will help us design experiments, build models, and develop appropriate metrics to deeply understand the strengths and weaknesses of our systems. They will build dashboards to automate data collection and reporting of relevant data streams, providing leadership and stakeholders with transparency into our system's performance. They will turn their findings into actions by writing detailed reports and providing recommendations on where we should focus our efforts to have the largest customer impact. A successful candidate should be a self-starter, comfortable with ambiguity with strong attention to detail, and have the ability to work in a fast-paced and ever-changing environment. They will also help coach/mentor junior scientists in the team. The ideal candidate should possess excellent verbal and written communication skills, capable of effectively communicating results and insights to both technical and non-technical audiences

Amazon launched the Generative AI Innovation Center (GenAIIC) in June 2023 to help AWS customers accelerate the use of generative AI to solve business and operational problems and promote innovation in their organization. This is a team of strategists, data scientists, engineers, and solution architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. (https://press.aboutamazon.com/2023/6/aws-announces- generative-ai-innovation-center). We’re looking for Data Scientists to use generative AI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. As an early-in-career joiner, you will initially join our A2C (Associate to Consultant) program for intensive training on AWS technology and delivery approach. Emirati nationality is required. Key job responsibilities As a Data Scientist, you will - Collaborate with AI/ML scientists, engineers, and architects to Research, design, develop, and evaluate cutting-edge generative AI algorithms to address real-world challenges - Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production - Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder - Provide customer and market feedback to Product and Engineering teams to help define product direction About the team The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train or fine tune the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The Generative AI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

You will be working with a unique and gifted team developing exciting products for consumers. The team is a multidisciplinary group of engineers and scientists engaged in a fast paced mission to deliver new products. The team faces a challenging task of balancing cost, schedule, and performance requirements. You should be comfortable collaborating in a fast-paced and often uncertain environment, and contributing to innovative solutions, while demonstrating leadership, technical competence, and meticulousness. Your deliverables will include development of thermal solutions, concept design, feature development, product architecture and system validation through to manufacturing release. You will support creative developments through application of analysis and testing of complex electronic assemblies using advanced simulation and experimentation tools and techniques. Key job responsibilities In this role, you will: - Evaluate and optimize thermal solution requirements of consumer electronic products - Use simulation tools like Star CCM/FloTherm XT/EFD for analysis and design of products - Validate design modifications for thermal concerns using simulation and actual prototypes - Establish temperature thresholds for user comfort level and component level considering reliability requirements - Have intimate knowledge of various materials and heat spreaders solutions to resolve thermal issues - Use of programming languages like Python and Matlab for analytical/statistical analyses and automation - Collaborate as part of device team to iterate and optimize design parameters of enclosures and structural parts to establish and deliver project performance objectives - Design and execute of tests using statistical tools to validate analytical models, identify risks and assess design margins - Create and present analytical and experimental results - Develop and apply design guidelines based on project learnings About the team Amazon Lab126 is an inventive research and development company that designs and engineers high-profile consumer electronics. Lab126 began in 2004 as a subsidiary of Amazon.com, Inc., originally creating the best-selling Kindle family of products. Since then, we have produced innovative devices like Fire tablets, Fire TV and Amazon Echo. What will you help us create?

The Artificial General Intelligence (AGI) team is looking for a highly skilled and experienced Applied Scientist, to support the development and implementation of state-of-the-art algorithms and models for supervised fine-tuning and reinforcement learning through human feedback and and complex reasoning; with a focus across text, image, and video modalities. As an Applied Scientist, you will play a critical role in supporting the development of Generative AI (Gen AI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. Key job responsibilities - Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in Gen AI - Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results - Think big about the arc of development of Gen AI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems - Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports

As a Survey Research Scientist within the Reputation Marketing & Insights team, your primary responsibility will be to help manage our employee communications research program, including a global tracking survey. The work will challenge you to be resourceful, think big while staying connected to the details, translate survey, focus group results, and advanced analytics into strategic direction, and embrace a high degree of change and ambiguity at speed. The scope and scale of what we strive to achieve is immense, but it is also meaningful and energizing. This is an individual contributor role. The right candidate possesses endless curiosity and passion for understanding employee perceptions and what drives them. You have end-to-end experience conducting qualitative research, robust large-scale surveys, campaign measurement, as well as advanced modeling skills to uncover perception drivers. You have proficiency in diving deep into large amounts of data and translating research into actionable insights/recommendations for internal communicators. You are an excellent writer who can effectively communicate data-driven insights and recommendations through written documents, presentations, and other internal communication channels. You are a creative problem-solver who seeks to deeply understand the business/communications so you can tailor research that informs stakeholder decision making and strategic messaging tactics. Key job responsibilities - Design and manage the execution of a global tracking survey focused on employee communications - Develop research to identify and test messages to drive employee perceptions - Use advanced statistical methodologies to better understand the relationship between key internal communications metrics and other related measures of perception (e.g., regression, structural equation modeling, latent growth curve modeling, Shapley analysis, etc.) - Develop causal and semi-causal measurement techniques to evaluate the perception impact of internal communications campaigns - Inform the design of an internal dashboard to visualize trends and incoming data - Identify opportunities to simplify existing research processes and operate more nimbly - Engage in strategic discussions with internal partner teams to ensure our research generates actionable and on-point findings