Senior Forward Deployed Engineer (Model Customization and Optimization)

What you'll do

• Set customer technical direction, success metrics, and roadmaps; lead engagement delivery and communicate risks and results.
• Design model customization, distributed training, reinforcement learning, and production inference approaches; optimize workloads on AWS Trainium.
• Mentor and lead engineers, oversee deliverables, and turn engagement results into reusable tools and influence AWS service roadmaps.

What they ask for

• 5+ years of non-internship professional software development experience and 5+ years programming with at least one software programming 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 deep learning model training, fine-tuning, or optimization experience; 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 and operating ML models in customer production environments, defining generative-model evaluation, or leading model optimization, post-training, or large-scale distributed training.

Pay

USD 193,300.00 - 261,500.00 annually (base salary); USD 168,100.00 - 227,400.00 annually (base salary); USD 184,900.00 - 250,200.00 annually (base salary); USD 168,100.00 - 227,400.00 annually (base salary); USD 168,100.00 - 227,400.00 annually (base salary)

Tools

PyTorch FSDP2, Megatron-LM, Miles, verl, SGLang, vLLM, AWS Trainium, AWS Neuron SDK

AI focus

Customize, post-train, evaluate, and optimize generative AI and foundation models, including reinforcement learning and agentic workflows; build and scale training and inference systems and migrate workloads to AWS Trainium.