Senior Forward Deployed Engineer (Model Customization and Optimization)

What you'll do

• Set customer technical direction, success metrics, and delivery plans for model customization and optimization engagements.
• Architect and optimize large-scale model training, post-training, and production inference, including migrations to AWS Trainium.
• Lead and mentor engagement teams, manage execution, and turn customer learnings into reusable tools and AWS service improvements.

What they ask for

• 5+ years of non-internship professional software development experience, including 5+ years programming in at least one language.
• 5+ years leading design or architecture of new and existing systems, including design patterns, reliability, and scaling.
• Experience as a mentor, tech lead, or engineering team lead.
• Hands-on experience training, fine-tuning, or optimizing deep learning models; ability to communicate technical concepts to technical and non-technical audiences, including senior leadership.

Nice to have

• Bachelor's degree in computer science or equivalent.
• Experience deploying ML models in customer production environments; defining generative-model evaluation; or leading model optimization, LLM post-training, or large-scale distributed LLM training.

Pay

USD 168,100.00 - 227,400.00 annually (base salary; USA, MA, Boston); USD 184,900.00 - 250,200.00 annually (base salary; USA, NY, New York); USD 168,100.00 - 227,400.00 annually (base salary; USA, VA, Arlington); USD 168,100.00 - 227,400.00 annually (base salary; USA, WA, Seattle)

Tools

PyTorch FSDP2, Megatron-LM, Miles, verl, SGLang, vLLM, NeMo Gym, OpenEnv

AI focus

Builds and customizes domain foundation models; performs fine-tuning, preference optimization, and reinforcement learning, including RL with verifiable rewards and multi-turn agentic RL; develops evaluation and synthetic-data strategies; optimizes model training and inference, including on AWS Trainium.