Careers

Amazon’s global talent management and compensation (GTMC) organization is looking for a Senior Applied Scientist to join our interdisciplinary science team. The role will lead our strategic science investments to develop and refine Generative AI solutions in our experiences that help more than 1.5 million employees build rewarding careers and shape how we manage Amazon's talent. GTMC is responsible for managing all aspects of Amazon employees' careers, from onboarding to exit. We build intelligent products that are used by employees, their managers and senior leadership to grow, develop and reward Amazon’s talent. The domains we cover include career development, talent evaluation, employee-role matching, promotions, organizational design and succession planning, and new areas that address the evolving needs of our diverse employee base. We are looking for an experienced applied scientist who has experience building, applying and customizing GenAI solutions to solve customer problems. As a senior applied scientist on the team, you will play a critical role in driving the development of GenAI technologies that handle Amazon-scale use cases and have a significant impact on our employees' lives. You will have the opportunity to lead exciting problems, publish and patent your work in one of the most high impact, innovative and unconventional applications of science in the People Experience and Technology space. If this kind of work excites you, reach out to us to find out more! Key job responsibilities - Provide scientific thought leadership in GenAI solution development for our science and engineering teams - Prototype and iterate on GenAI solutions for capabilities across writing feedback, summarization, information retrieval, content generation and orchestration. - Participate in scoping feature and business planning roadmap of GTMC’s science investments - Design and execute science-based product ideas and features, project plans and communicate with stakeholders - Partner with engineers to productionize GenAI and other science models at the scale of Amazon - Mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the team About the team GTMC's science team is an experienced central interdisciplinary organization of scientists spanning machine learning, economics and research that builds science models for Amazon's worldwide employee-facing talent management products, designs and supports experiments for product features, and measures impact of product and program initiatives across the broader organization. Examples of our work include GenAI-powered summarization and writing assistants, content and people recommendation systems, scalable experimentation products and measuring organizational north star metrics.

The Data Scientist in NLP within Customer Engagement Tech, Self-Service and Automation team will work on the research, design, and implementation of solutions to key challenges in developing, evaluating and deploying solutions based on large pretrained language models into conversational AI systems that can understand and communicate with customers in a natural and contextually appropriate manner. This involves model development in areas such as multi-turn dialogue management, knowledge grounding, and open-ended generation and assessment of dialogue quality and style of the conversational model. Key job responsibilities • Define and implement robust HITL strategies to effectively expedite LLM models scaling process. • Collaborate with human annotators and subject matter experts to establish clear guidelines and quality control measures. • Analyze feedback loops and iterate on model performance to ensure continuous improvement. • Conduct in-depth analysis of large-scale conversational datasets to identify patterns, trends, and potential challenges. • Independently document methodologies, findings, and results in a clear and concise manner, ensuring reproducibility and knowledge sharing. • Collaborate with cross-functional teams, including applied scientists, software engineers, and product managers, to integrate LLM-based solutions into Amazon's customer service platforms. • Develop and implement strategies for data collection, annotation, and model training to ensure high-quality and robust performance of the chatbots. • Conduct experiments and evaluations to measure the performance of the developed models and systems, and identify areas for improvement. Stay up-to-date with the latest advancements in NLP, LLMs, and conversational AI, and explore opportunities to incorporate new techniques and technologies into Amazon's customer service solutions. A day in the life We thrive on solving challenging problems to innovate for our customers. By pushing the boundaries of technology, we create unparalleled experiences that enable us to rapidly adapt in a dynamic environment. Our decisions are guided by data, and we collaborate with engineering, science, and product teams to foster an innovative learning environment 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! Benefits Summary: 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: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan About the team Join our team of scientists and engineers who develop and deploy LLM-based Conversational AI systems to enhance Amazon's customer service experience and effectiveness. We work on innovative solutions that help customers solve their issues and get their questions answered efficiently, and associate-facing products that support our customer service associate workforce.

The Data Scientist in NLP within Customer Engagement Tech, Self-Service and Automation team will work on the research, design, and implementation of solutions to key challenges in developing, evaluating and deploying solutions based on large pretrained language models into conversational AI systems that can understand and communicate with customers in a natural and contextually appropriate manner. This involves model development in areas such as multi-turn dialogue management, knowledge grounding, and open-ended generation and assessment of dialogue quality and style of the conversational model. Key job responsibilities • Define and implement robust HITL strategies to effectively expedite LLM models scaling process. • Collaborate with human annotators and subject matter experts to establish clear guidelines and quality control measures. • Analyze feedback loops and iterate on model performance to ensure continuous improvement. • Conduct in-depth analysis of large-scale conversational datasets to identify patterns, trends, and potential challenges. • Independently document methodologies, findings, and results in a clear and concise manner, ensuring reproducibility and knowledge sharing. • Collaborate with cross-functional teams, including applied scientists, software engineers, and product managers, to integrate LLM-based solutions into Amazon's customer service platforms. • Develop and implement strategies for data collection, annotation, and model training to ensure high-quality and robust performance of the chatbots. • Conduct experiments and evaluations to measure the performance of the developed models and systems, and identify areas for improvement. Stay up-to-date with the latest advancements in NLP, LLMs, and conversational AI, and explore opportunities to incorporate new techniques and technologies into Amazon's customer service solutions. A day in the life We thrive on solving challenging problems to innovate for our customers. By pushing the boundaries of technology, we create unparalleled experiences that enable us to rapidly adapt in a dynamic environment. Our decisions are guided by data, and we collaborate with engineering, science, and product teams to foster an innovative learning environment 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! Benefits Summary: 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: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan About the team Join our team of scientists and engineers who develop and deploy LLM-based Conversational AI systems to enhance Amazon's customer service experience and effectiveness. We work on innovative solutions that help customers solve their issues and get their questions answered efficiently, and associate-facing products that support our customer service associate workforce.

The Data Scientist in NLP within Customer Engagement Tech, Self-Service and Automation team will work on the research, design, and implementation of solutions to key challenges in developing, evaluating and deploying solutions based on large pretrained language models into conversational AI systems that can understand and communicate with customers in a natural and contextually appropriate manner. This involves model development in areas such as multi-turn dialogue management, knowledge grounding, and open-ended generation and assessment of dialogue quality and style of the conversational model. Key job responsibilities • Define and implement robust HITL strategies to effectively expedite LLM models scaling process. • Collaborate with human annotators and subject matter experts to establish clear guidelines and quality control measures. • Analyze feedback loops and iterate on model performance to ensure continuous improvement. • Conduct in-depth analysis of large-scale conversational datasets to identify patterns, trends, and potential challenges. • Independently document methodologies, findings, and results in a clear and concise manner, ensuring reproducibility and knowledge sharing. • Collaborate with cross-functional teams, including applied scientists, software engineers, and product managers, to integrate LLM-based solutions into Amazon's customer service platforms. • Develop and implement strategies for data collection, annotation, and model training to ensure high-quality and robust performance of the chatbots. • Conduct experiments and evaluations to measure the performance of the developed models and systems, and identify areas for improvement. Stay up-to-date with the latest advancements in NLP, LLMs, and conversational AI, and explore opportunities to incorporate new techniques and technologies into Amazon's customer service solutions. A day in the life We thrive on solving challenging problems to innovate for our customers. By pushing the boundaries of technology, we create unparalleled experiences that enable us to rapidly adapt in a dynamic environment. Our decisions are guided by data, and we collaborate with engineering, science, and product teams to foster an innovative learning environment 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! Benefits Summary: 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: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan About the team Join our team of scientists and engineers who develop and deploy LLM-based Conversational AI systems to enhance Amazon's customer service experience and effectiveness. We work on innovative solutions that help customers solve their issues and get their questions answered efficiently, and associate-facing products that support our customer service associate workforce.

The Data Scientist in NLP within Customer Engagement Tech, Self-Service and Automation team will work on the research, design, and implementation of solutions to key challenges in developing, evaluating and deploying solutions based on large pretrained language models into conversational AI systems that can understand and communicate with customers in a natural and contextually appropriate manner. This involves model development in areas such as multi-turn dialogue management, knowledge grounding, and open-ended generation and assessment of dialogue quality and style of the conversational model. Key job responsibilities 1. Lead the development of LLM-based chatbots and conversational AI systems for customer service applications. 2. Implement state-of-the-art NLP and ML models for tasks such as language understanding, dialogue management, and response generation and dialogue quality assessment. 3. Collaborate with cross-functional teams, including applied scientists, software engineers, and product managers, to integrate LLM-based solutions into Amazon's customer service platforms. 4. Develop and implement strategies for data collection, annotation, and model training to ensure high-quality and robust performance of the chatbots. 5. Conduct experiments and evaluations to measure the performance of the developed models and systems, and identify areas for improvement. 6. Stay up-to-date with the latest advancements in NLP, LLMs, and conversational AI, and explore opportunities to incorporate new techniques and technologies into Amazon's customer service solutions. A day in the life We thrive on solving challenging problems to innovate for our customers. By pushing the boundaries of technology, we create unparalleled experiences that enable us to rapidly adapt in a dynamic environment. Our decisions are guided by data, and we collaborate with engineering, science, and product teams to foster an innovative learning environment 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! Benefits Summary: 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: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan About the team Join our team of scientists and engineers who develop and deploy LLM-based Conversational AI systems to enhance Amazon's customer service experience and effectiveness. We work on innovative solutions that help customers solve their issues and get their questions answered efficiently, and associate-facing products that support our customer service associate workforce.

Amazon AI is looking for an Applied Scientist to join our science team in the area of Multimodal Learning, Large Language Models, Natural Language Processing and Speech/Audio Representation Learning. Our organization develops the science that drives the cloud-based AI services of AWS. Our mission is to put the power of AI into the hands of every developer. We seek to advance the state of the art in machine learning to create services that delight our customers and meet real-world business needs. As an Applied Scientist you will partner with talented scientists and engineers to design, train, test, and deploy machine learning models. You will contribute to innovative features, improve our services based on customer requirements and help maintain a highly scalable data and model management infrastructure that supports cutting-edge research. You will be responsible for translating business and engineering requirements into deliverables and software products. We are looking for candidates who thrive in an exciting, fast-paced environment and who have a strong personal interest in learning, researching, and creating new technologies with high customer impact. Prior domain knowledge in multimodal learning, unsupervised speech/audio representations, natural language processing, or computer vision is strongly preferred; solid knowledge of fundamentals of statistics, machine learning, and deep learning is required. Candidates should possess strong software engineering skills and several years of industry experience. About the team About AWS 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 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. This team is part of AWS Utility Computing: Utility Computing (UC) AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.

We are seeking an innovative and technically strong data scientist with a background in optimization, machine learning, and statistical modeling/analysis. This role requires a team member to have strong quantitative modeling skills and the ability to apply optimization/statistical/machine learning methods to complex decision-making problems, with data coming from various data sources. The candidate should have strong communication skills, be able to work closely with stakeholders and translate data-driven findings into actionable insights. The successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and ability to work in a fast-paced and ever-changing environment. Key job responsibilities 1. Ability to understand a business problem and the available data and identify what statistical or ML techniques can be applied to answer a business question 2. Given a business problem, estimate solution feasibility and potential approaches based on available data 3. Understand what data is available, where, and how to pull it together. Work with partner teams where needed to facilitate permissions and acquisition of required data 4. Quickly prototype solutions and build models to test feasibility of solution approach 5. Build statistical models/ ML models, train and test them to and drive towards the optimal level of model performance 6. Improve existing processes with development and implementation of state of the art generative AI models 7. Work with technology teams to integrate models by wrapping them as services that plug into Amazon's Alexa Eco system 8. Work across the spectrum of reporting and data visualization, statistical modeling and supervised learning tools and techniques and apply the right level of solution to the right problem About the team Alexa Communications (connecting friends and family) is looking for a Data Scientist to join our team in the area of speech and large language model. We are seeking a candidate with strong analytical skills and language technology experience to help us measure, analyze and solve complex problems. In this role, you are responsible for the design and delivery of Language Understanding using your linguistic, voice user interface (VUI) design, and data analysis skills to understand what a customer meant. You are a key member in new feature development while proactively improving existing experiences. You work closely with other Engineers, Product Managers, Scientists and Engineers to deliver magical experiences that customers love.

AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help. You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. In 2019, Amazon co-founded The Climate Pledge and made a commitment to achieve net-zero carbon by 2040 —10 years ahead of the Paris Agreement. We invited others to join us and there are now more than 300 businesses and organizations across 51 industries and 29 countries that have signed the Pledge, which means we are collectively coming at the climate crisis from nearly every sector and nearly every angle. As part of our efforts to decarbonize our business, we became the world’s largest corporate purchaser of renewable energy in 2020, and last year, we reached 85% renewable energy across our business, and are on a path to power our operations with 100% renewable energy by 2025. We recently announced that AWS will be water positive by 2030, returning more water to communities than it uses in its direct operations. The company also announced its 2021 global water use efficiency (WUE) metric of 0.25 liters of water per kilowatt-hour, demonstrating AWS’s leadership in water efficiency among cloud providers. To learn more about AWS’s water+ commitment visit: Water Stewardship. Come join the team that is building the tools and innovative technology to manage our growing portfolio of renewable energy investments, including solar, on-shore and off-shore wind farms. Key job responsibilities As an data scientist, you will employ machine learning and analytics to create scalable solutions for problems in sustainable energy space. You will dissect large historical business data sets to enhance and streamline essential processes. You will partner with data and software teams to create models for predictive insights and establish automated methods for large data analysis. A day in the life To learn more, you can visit: amazon sustainability in the cloud About the team 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. 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.

The Measurement, Ad Tech, and Data Science (MADS) team at Amazon Ads is at the forefront of developing cutting-edge solutions that help our tens of millions of advertisers understand the value of their ad spend while prioritizing customer privacy and measurement quality. We develop cutting-edge deterministic algorithms, machine learning models, causal models, and statistical approaches to empower advertisers with insights on the effectiveness of their ads in guiding customers from awareness to purchases. Our insights help advertisers build full-funnel advertising strategies. We maximize the information we extract from incomplete traffic signals and alternative sources to capture the impact of their ad spending for both Amazon recognized and anonymous traffic. Our vision is to lead the industry in extracting and combining information from several sources to enable advertisers to optimize their return on their ad spend. As a Senior Applied Scientist on the team, you will be at the fore-front of innovation, developing measurement solutions end-to-end from inception to production. You will set the technical vision and innovate on behalf of our customers. You will propose, design, analyze, and productionize models to provide novel measurement insights to our customers. You will partner with engineering to deploy these solutions into production. You will work with key stakeholders from various business teams to enable advertisers to act upon those metrics. Key job responsibilities * Lead the development of ad measurement models and solutions that address the full spectrum of an advertiser's investment, focusing on scalable and efficient methodologies. * Collaborate closely with cross-functional teams including engineering, product management, and business teams to define and implement measurement solutions. * Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop cutting-edge models that measure the impact of ad spend across multiple platforms and timescales. * Drive experimentation and the continuous improvement of ML models through iterative development, testing, and optimization. * Translate complex scientific challenges into clear and impactful solutions for business stakeholders. * Mentor and guide junior scientists, fostering a collaborative and high-performing team culture. * Foster collaborations between scientists to move faster, with broader impact. * Regularly engage with the broader scientific community with presentations, publications, and patents. A day in the life You will solve real-world problems by getting and analyzing large amounts of data, generate business insights and opportunities, design simulations and experiments, and develop statistical and ML models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the advertising organization. You will prepare written and verbal presentations to share insights to audiences of varying levels of technical sophistication. Team video https://advertising.amazon.com/help/G4LNN5YWHP6SM9TJ

Are you excited about leveraging state-of-the-art Computer Vision algorithms and large datasets to solve real-world problems? Join Amazon as an Applied Scientist Intern and be at the forefront of AI innovation! As an Applied Scientist Intern, you'll work in a fast-paced, cross-disciplinary team of pioneering researchers. You'll tackle complex problems, developing solutions that either build on existing academic and industrial research or stem from your own innovative thinking. Your work may even find its way into customer-facing products, making a real-world impact. Key job responsibilities - Develop novel solutions and build prototypes - Work on complex problems in Computer Vision and Machine Learning - Contribute to research that could significantly impact Amazon's operations - Collaborate with a diverse team of experts in a fast-paced environment - Collaborate with scientists on writing and submitting papers to Tier-1 conferences (e.g., CVPR, ICCV, NeurIPS, ICML) - Present your research findings to both technical and non-technical audiences Key Opportunities: - Collaborate with leading machine learning researchers - Access cutting-edge tools and hardware (large GPU clusters) - Address challenges at an unparalleled scale - Become a disruptor, innovator, and problem solver in the field of computer vision - Potentially deliver solutions to production in customer-facing applications - Opportunities to become an FTE after the internship Join us in shaping the future of AI at Amazon. Apply now and turn your research into real-world solutions!