Machine Learning Engineer, Model Customization, Generative AI Innovation Center

The Generative AI Innovation Center at AWS is at the forefront of empowering customers to leverage cutting-edge AI technologies for transformative business opportunities. As a Machine Learning Engineer on our team, you'll be responsible for developing custom Large Language Models (LLMs) across various domains and modalities. The role involves designing distributed training pipelines, fine-tuning state-of-the-art LLMs, and optimizing models for AWS's custom AI accelerators.

You'll work within a multidisciplinary team of strategists, scientists, engineers, and architects, collaborating directly with enterprise customers to develop tailored generative AI solutions. The position offers unique opportunities to innovate with large-scale AI systems and impact top AWS clients' AI initiatives.

Key technical responsibilities include implementing distributed training pipelines using advanced tools like FSDP and DeepSpeed, adapting LLMs through continued pre-training and RLHF, and optimizing models for AWS Silicon using the Neuron SDK. You'll also develop custom kernels for enhanced performance and work closely with foundational model providers.

AWS values diverse experiences and maintains an inclusive culture through employee-led affinity groups and ongoing learning opportunities. The company offers strong mentorship, career growth resources, and emphasizes work-life harmony. As part of AWS, you'll be working with the world's most comprehensive cloud platform, contributing to continuous innovation in cloud computing.

This role requires 3+ years of professional software development experience and strong expertise in machine learning, particularly in training and fine-tuning models. The ideal candidate will have hands-on experience with generative AI technology and proficiency in modern programming languages.