ML Engineer, Generative AI Innovation Center

Description The Generative AI Innovation Center at AWS empowers customers to harness state of the art AI technologies for transformative business opportunities. Our multidisciplinary team of strategists, scientists, engineers, and architects collaborates with customers across industries to fine-tune and deploy customized generative AI applications at scale. Additionally, we work closely with foundational model providers to optimize AI models for Amazon Silicon, enhancing performance and efficiency. As an ML Engineer on our team, you will work with clients, partners and other AWS teams to drive the development of custom Large Language Models (LLMs) across languages, domains, and modalities. You will be responsible for fine-tuning state-of-the‑art LLMs for diverse use cases while optimizing models for high-performance deployment on AWS's custom AI accelerators. This role offers an opportunity to innovate at the forefront of AI, tackling end‑to‑end LLM training pipelines at massive scale and delivering next‑generation AI solutions for top AWS clients. Key job responsibilities Large-Scale Training Pipelines: Design and implement distributed training pipelines for LLMs using tools such as Fully Sharded Data Parallel (FSDP) and DeepSpeed, ensuring scalability and efficiency. LLM Customization & Fine‑Tuning: Adapt LLMs for new languages, domains, and vision applications through continued pre‑training, fine‑tuning, and Reinforcement Learning with Human Feedback (RLHF). Model Optimization on AWS Silicon: Optimize AI models for deployment on AWS Inferentia and Trainium, leveraging the AWS Neuron SDK and developing custom kernels for enhanced performance. Customer Collaboration: Interact with enterprise customers and foundational model providers to understand their business and technical challenges, co‑developing tailored generative AI solutions. Define path to production for generative AI solutions and implement large scale production generative AI solutions. About the team We value 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 We foster a culture of inclusion that empowers us to be proud of our differences. Ongoing events and learning experiences 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. Endless knowledge-sharing, mentorship, and other career‑advancing resources 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. Basic Qualifications 3+ years of non‑internship professional software development experience. 2+ years of non‑internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience. Experience programming with at least one software programming language. Hands‑on experience with deep learning and/or machine learning methods (e.g. for training, fine tuning, and inference). Hands‑on experience with generative AI technology. Preferred Qualifications Hands‑on experience with at least one ML library or framework. 2+ years of professional experience in developing, deploying or optimizing ML models. 2+ years of professional experience in the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations. Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. Please consult our Privacy Notice to know more about how we collect, use and