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Machine Learning Engineer, Model Customization, Generative AI Innovation Center

Amazon Web Services (AWS)

$129,300 - $223,600
Dec 20, 2025
Seattle, WA, US
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The Generative AI Innovation Center at AWS is looking to empower customers to harness state of the art AI technologies for transformative business opportunities by developing custom Large Language Models (LLMs) across languages, domains, and modalities.

Requirements

  • 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
  • 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
  • Programming with at least one software programming language experience
  • Experience hands-on experience with developing, deploying, or optimizing machine learning models using a recognized ML library or framework

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

Other

  • 3+ years of non-internship professional software development experience
  • Bachelor's degree in computer science or equivalent
  • Work safely and cooperatively with other employees, supervisors, and staff
  • Adhere to standards of excellence despite stressful conditions
  • Communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service