Careers

Amazon launched the Generative AI Innovation Center (GAIIC) 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 (https://press.aboutamazon.com/2023/6/aws-announces-generative-ai-innovation-center). GAIIC provides opportunities to innovate in a fast-paced organization that contributes to game-changing projects and technologies that get deployed on devices and in the cloud. Key job responsibilities As an Applied Science Manager in GAIIC, you'll partner with technology and business teams to build new GenAI solutions that delight our customers. You will be responsible for directing a team of data/research/applied scientists, deep learning architects, and ML engineers to build generative AI models and pipelines, and deliver state-of-the-art solutions to customer’s business and mission problems. Your team will be working with terabytes of text, images, and other types of data to address real-world problems. The successful candidate will possess both technical and customer-facing skills that will allow you to be the technical “face” of AWS within our solution providers’ ecosystem/environment as well as directly to end customers. You will be able to drive discussions with senior technical and management personnel within customers and partners, as well as the technical background that enables them to interact with and give guidance to data/research/applied scientists and software developers. The ideal candidate will also have a demonstrated ability to think strategically about business, product, and technical issues. Finally, and of critical importance, the candidate will be an excellent technical team manager, someone who knows how to hire, develop, and retain high quality technical talent. AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services. About the team AWS Global Services includes experts from across AWS who help our customers design, build, operate, and secure their cloud environments. Customers innovate with AWS Professional Services, upskill with AWS Training and Certification, optimize with AWS Support and Managed Services, and meet objectives with AWS Security Assurance Services. Our expertise and emerging technologies include AWS Partners, AWS Sovereign Cloud, AWS International Product, and the Generative AI Innovation Center. You’ll join a diverse team of technical experts in dozens of countries who help customers achieve more with the AWS cloud. 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.

Amazon Science gives you insight into the company’s approach to customer focused scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work. Please visit https://www.amazon.science for more information. Are you an expert in Neural Network, Graph Models and Probabilistic Risk Modeling? Are you interested in building AI-driven solutions on complex business problems that have significant global benefit. The Brand Protection ML team designs and builds high performance AI systems using machine learning that identify fraudulent and abusive entities to protect customers, brands, selling partners and the Amazon store worldwide from counterfeit and other forms of IP infringements. We are looking for a highly talented scientist to help build of our vision for Brand Protection. As an applied scientist on the team, You will play a key role in designing, developing, and deploying advanced graph-based models that detect hidden relationships, anomalous behaviors, and emerging risks in large-scale, complex data environments. You will work backwards from data insights and customer feedback to build the right machine learning solutions, and resourceful in finding innovative solutions to unsolved problems. You will work closely will product team and engineering partners to launch the solution into production and owning the end-to-end solution. An ideal candidate should have hands-on experience developing end-to-end Machine Learning solutions at industrial setting, specially in graph-based algorithms (e.g., Graph Neural Networks, representation learning, community detection, link prediction) for fraud and risk detection, from conception to launch in a rapidly evolving environment. Amazon’s growth requires leaders who move fast, have an entrepreneurial spirit to create new solutions, have an unrelenting tenacity to get things done, and are capable of breaking down and solving complex problems. Major responsibilities: - Understand business challenges by analyzing data and customer feedback - Collaborate with tech and product teams on building ML strategies, experimentation, implementation and continuous improvement post-launch - Analyze and extract relevant information from large amounts of both structured and unstructured data to design strategies to solve business problems. - Develop and apply graph-based algorithms (e.g., Graph Neural Networks, representation learning, community detection, link prediction) for fraud and risk detection. - Design scalable data pipelines to construct, enrich, and maintain large-scale knowledge graphs from heterogeneous data sources. - Present research and analytics insights with stakeholders and partners to advance organizational science knowledge and decision making - Research and implement novel AI solutions and publish research papers internally (and externally where appropriate) About the team Here at Selling Partner Services, we embrace our differences. We are committed to furthering our culture of inclusion. We have 14 employee-led affinity groups, reaching 10,000+ employees in chapters globally. We have innovative benefit offerings, and we host annual and ongoing learning experiences, including our DEI Ambassador Program. 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.

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 limits. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams. We are seeking a Sr. Manager, Applied Science to lead and build our science team focused on machine learning applications in life sciences. The role combines scientific leadership with people management responsibilities to drive innovative solutions. The role requires balancing exploratory research with delivering production-ready solutions while maintaining high scientific standards. You will work with Amazon's large-scale computing resources to accelerate advances in machine learning applications. Key job responsibilities - Lead ML for life science efforts using computational design approaches and ML-based tools. - Guide teams in applying SOTA ML methods, experimentation design, and modeling approaches. - Transform complex real world problems into scientific challenges and allocate resources effectively. - Review requirements, conduct technical architecture reviews, and make informed judgments around technical and business tradeoffs. - Provide mentorship to Applied Scientists, Research Scientists and Data Scientists while maintaining scientific rigor. - Manage hiring, performance feedback, promotions, and team development. - Collaborate with cross functional teams.

About Amazon Advertising: Amazon Advertising operates at the intersection of eCommerce and advertising, offering a rich array of digital display advertising solutions with the goal of helping our customers find and discover anything they want to buy. We help advertisers of all types to reach Amazon customers on Amazon.com, across our other owned and operated sites, on other high quality sites across the web, and on millions of mobile devices. We start with the customer and work backwards in everything we do, including advertising. If you’re interested in joining a rapidly growing team working to build a unique, world-class advertising group with a relentless focus on the customer, you’ve come to the right place. About our team: Our team, CreativeX optimizations, is responsible for tailoring the visual experience of ads to each context in real time. To accomplish this, we are investing in latent-diffusion models, large language models (LLM), reinforced learning (RL), Computer Vision, and related methods. Key job responsibilities We are looking for talented Applied Scientists who are adept at a variety of skills, especially with reinforcement learning and recommendations, and familiarity with LLMs, latent diffusion, or related foundational models that will accelerate our plans to dynamically optimize ad creatives on behalf of advertisers. Every member of the team is expected to build customer (advertiser) facing features, contribute to the collaborative spirit within the team, publish, patent, and bring state-of-the-art research to raise the bar within the team.

Hardware Silicon and Systems Group leads the development and optimization of on-device ML models for Amazon's hardware products, including audio, vision, and multi-modal AI features. We work at the critical intersection of ML innovation and silicon design, ensuring AI capabilities can run efficiently on resource-constrained devices. Currently, we enable production ML models across multiple device families, including Echo, Ring/Blink, and other consumer devices. Our work directly impacts Amazon's customer experiences in consumer AI device market. The solutions we develop determine which AI features can be offered on-device versus requiring cloud connectivity, ultimately shaping product capabilities and customer experience across Amazon's hardware portfolio. This is a unique opportunity to help shape the future of AI in consumer devices at unprecedented scale. You'll be at the forefront of developing industry-first model architectures and compression techniques that will power AI features across millions of Amazon devices worldwide. Your innovations will directly enable new AI features that enhance how customers interact with Amazon products every day. As Principal Applied Scientist you will blend expertise at the intersection of ML and hardware optimization for model training, build cutting-edge architectures for vision, language, and multi-modal tasks. Role requires a specialist in hardware-aware quantization, with hands-on experience in model compression techniques like pruning and distillation. You will be responsible for computer architecture, ML accelerator designs, efficient inference algorithms and low-precision arithmetic. Key job responsibilities As a Principal Applied Scientist, you will: • Own the technical architecture and optimization strategy for ML models deployed across Amazon's device ecosystem, from existing to yet-to-be-shipped products. • Develop novel model architectures optimized for our custom silicon, establishing new methodologies for model compression and quantization. • Create an evaluation framework for model efficiency and implement multimodal optimization techniques that work across vision, language, and audio tasks. • Define technical standards for model deployment and drive research initiatives in model efficiency to guide future silicon designs. • Spend the majority of your time doing deep technical work - developing novel ML architectures, writing critical optimization code, and creating proof-of-concept implementations that demonstrate breakthrough efficiency gains. • Influence architecture decisions impacting future silicon generations, establish standards for model optimization, and mentor others in advanced ML techniques.

Application deadline: Applications will be accepted on an ongoing basis Amazon Ads is re-imagining advertising through cutting-edge generative AI technologies. We combine human creativity with artificial intelligence to transform every aspect of the advertising lifecycle – from ad creation and optimization to performance analysis and customer insights. Our solutions help advertisers grow their brands while enabling millions of customers to discover and purchase products through delightful experiences. We deliver billions of ad impressions and millions of clicks daily, breaking fresh ground in product and technical innovations. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. Key job responsibilities As an Applied Scientist in Amazon Ads, you will: - Research and implement cutting-edge ML approaches, including applications of generative AI and large language models - Develop and deploy innovative ML solutions spanning multiple disciplines – from ranking and personalization to natural language processing, computer vision, recommender systems, and large language models - Drive end-to-end projects that tackle ambiguous problems at massive scale, often working with petabytes of data - Build and optimize models that balance multiple stakeholder needs - helping customers discover relevant products while enabling advertisers to achieve their goals efficiently - Build ML models, perform proof-of-concept, experiment, optimize, and deploy your models into production, working closely with cross-functional teams including engineers, product managers, and other scientists - Design and run A/B experiments to validate hypotheses, gather insights from large-scale data analysis, and measure business impact - Develop scalable, efficient processes for model development, validation, and deployment that optimize traffic monetization while maintaining customer experience A day in the life Why you will love this role: This role offers unprecedented breadth in ML applications, and access to extensive computational resources and rich datasets that enable you to build truly innovative solutions. You'll work on projects that span the full advertising lifecycle - from sophisticated ranking algorithms and real-time bidding systems to creative optimization and measurement solutions. You'll also work alongside talented engineers, scientists and product leaders in a culture that encourages innovation, experimentation, and bias for action where you’ll directly influence business strategy through your scientific expertise. What makes this role unique is the combination of scientific rigor with real-world impact. You’ll re-imagine advertising through the lens of advanced ML while solving problems that balance the needs of advertisers, customers, and Amazon's business objectives. About the team Your impact and career growth: Amazon Ads is investing heavily in AI and ML capabilities, creating opportunities for scientists to innovate and make their mark. Your work will directly impact millions. Whether you see yourself growing as an individual contributor or moving into people management, there are clear paths for career progression. This role combines scientific leadership, organizational ability, technical strength, and business understanding. You'll have opportunities to lead technical initiatives, mentor other scientists, and collaborate with senior leadership to shape the future of advertising technology. Most importantly, you'll be part of a community that values scientific excellence and encourages you to push the boundaries of what's possible with AI. Watch two applied scientists at Amazon Ads talk about their work: https://www.youtube.com/watch?v=vvHsURsIPEA Learn more about Amazon Ads: https://advertising.amazon.com/

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Senior Applied Scientist; to lead the development and implementation of Generative AI (GenAI) algorithms and models for supervised fine-tuning, and advance the state of the art with Large Language Models (LLMs), As a Senior Applied Scientist, you will play a critical role in driving the development of GenAI 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 GenAI - 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 GenAI 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 - Mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the team

The Artificial General Intelligence (AGI) team is looking for a Senior Applied Scientist to work on pre-training methodologies for Generative Artificial Intelligence (GenAI) models. You will interact closely with our customers and with the academic and research communities. You will be at the heart of a growing and exciting focus area for Amazon, working with other acclaimed engineers and world-famous scientists. Key job responsibilities Join us to work as an integral part of a team that has diverse experience with GenAI models in this space. We work on these areas: - Scaling laws - Hardware-informed efficient model architecture, low-precision training - Optimization methods, learning objectives, curriculum design - Deep learning theories on efficient hyperparameter search and self-supervised learning - Learning objectives and reinforcement learning methods - Distributed training methods and solutions - AI-assisted research About the team The AGI team has a mission to push the envelope in Large Language Models (LLMs) and multimodal systems, in order to provide the best-possible experience for our customers.

Revolutionize logistics through groundbreaking data science at Amazon! We're seeking an innovative problem-solver who will transform complex global logistics challenges using advanced analytics and artificial intelligence. Your work will directly impact how millions of packages move worldwide, leveraging cutting-edge machine learning, Large Language Models (LLMs), and predictive technologies to optimize our intricate delivery networks. Our team empowers data-driven decision-making by developing sophisticated analytical solutions that bridge operational insights with strategic vision. You'll have the opportunity to design scalable models, implement advanced AI technologies, and create transformative recommendations that reshape logistics efficiency at a global scale. Key job responsibilities • Build sophisticated machine learning models and production pipelines to analyze complex logistics data • Develop advanced AI solutions using Python, AWS tools, and emerging technologies like Large Language Models • Synthesize information from diverse data sources to generate meaningful, actionable business insights • Collaborate with cross-functional teams to translate complex technical findings into strategic recommendations • Design and implement optimization strategies that enhance network performance and operational efficiency A day in the life As a Data Scientist in our R2L team, you'll immerse yourself in intricate data ecosystems, uncovering hidden patterns and opportunities that can revolutionize package delivery. Your daily work will involve exploring massive datasets, developing innovative analytical approaches, building production pipelines and transforming raw information into strategic intelligence. About the team We are a dynamic collective of data enthusiasts dedicated to optimizing Amazon's logistics infrastructure. Our team operates at the intersection of technology, operations, and strategic innovation, working collaboratively to create more intelligent, responsive, and efficient delivery systems.

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? The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. Starting in 2024, the Innovation Center launched a new Custom Model and Optimization program to help customers develop and scale highly customized generative AI solutions. The team helps customers imagine and scope bespoke use cases that will create the greatest value for their businesses, define paths to navigate technical or business challenges, develop and optimize models to power their solutions, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently. 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. We’re looking for Applied Scientists capable of using GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. Key job responsibilities As an Applied Scientist, you will • Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions to address real-world challenges • Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production • Help customers optimize their solutions through approaches such as model selection, training or tuning, right-sizing, distillation, and hardware optimization • Provide customer and market feedback to product and engineering teams to help define product direction