Forward Deployed Engineer (Model Customization and Optimization), AWS Forward Deployed Engineering

What you'll do

• Translate customer goals into evaluation criteria and technical plans; build data pipelines, training workflows, evaluation harnesses, and production serving systems.
• Post-train and optimize models for quality, latency, throughput, memory use, and cost; migrate workloads to AWS Trainium and address performance and accuracy gaps.
• Create reusable tools and patterns, share field learnings with AWS service teams, and identify opportunities to expand customer engagements; travel up to 25%.

What they ask for

• 3+ years of non-internship professional software development experience.
• 2+ years of non-internship experience in design or architecture of new and existing systems, including design patterns, reliability, and scaling.
• Experience programming in at least one software programming language.
• Hands-on experience with generative AI technology, such as LLMs, vision-language models, or speech models.

Nice to have

• Bachelor's degree in computer science or equivalent.
• Experience with distributed LLM training, post-training, model optimization, or deploying and operating ML models in customer production environments.

Pay

143,700.00 - 194,400.00 USD annually (base salary; Boston); 158,100.00 - 213,800.00 USD annually (base salary; New York); 143,700.00 - 194,400.00 USD annually (base salary; Arlington); 143,700.00 - 194,400.00 USD annually (base salary; Seattle)

Tools

PyTorch FSDP2, Megatron-LM, SGLang, vLLM, AWS Trainium, AWS Neuron SDK, Amazon Bedrock, Amazon SageMaker AI

AI focus

Customizes and post-trains generative AI models, including supervised fine-tuning, preference optimization, and reinforcement learning; builds evaluation, training, and inference systems and optimizes models for production.