Embedded GenAI Model Engineer | Custom Training & Optimization

Amazon Inc.; East Palo Alto (CA); On-site; USD 165,000 - 224,000; Full time

Job summary

Amazon Web Services, Inc. is seeking a Forward Deployed Engineer II to embed with customer teams, defining evaluation bars, preparing data, and guiding end-to-end customization and deployment of generative AI models in production.

You will optimize training, inference, and serving architectures across open-weight foundation models and domain-specific adaptations. The role emphasizes hands-on model customization, large-scale training/inference systems, and performance tuning on AWS chips, with

Qualifications

• 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.
• Hands-on experience with generative AI technology, such as LLMs, vision-language models, or speech models.

Responsibilities

• Embed within customer ML and engineering teams: Understand the customer's business, data, model stack, and operational constraints. Translate ambiguous goals into a measurable evaluation bar and a technical plan for your workstream such as model selection, customization approach, and serving architecture.
• Customize and post-train models. Adapt open-weight and foundation models to customer domains through continued pre-training, supervised fine-tuning, preference optimization, and reinforcement learning (including RLHF, RL with verifiable rewards, and multi-turn agentic RL). Build the data pipelines, synthetic data generation, and evaluation harnesses that prove a customized model out performs the baseline on the customer's own quality, latency, and cost bar.
• Build large-scale training and inference systems. Design and implement distributed training and RL post-training pipelines using frameworks such as PyTorch FSDP2, Megatron-LM, Miles, and verl.
• Optimize models on AWS chips. Migrate and tune training and inference workloads for AWS Trainium using the AWS Neuron SDK.
• Accelerate impact beyond the engagement. Codify reusable fine-tuning recipes, evaluation frameworks, benchmarking tools, and optimization patterns.

Skills

Software development

Generative AI

PyTorch

Distributed systems

Education

Bachelor’s degree in computer science or equivalent

Tools

PyTorch FSDP2

Megatron-LM

NeMo

Job description

Amazon Web Services, Inc. is seeking a Forward Deployed Engineer II to embed with customer teams, defining evaluation bars, preparing data, and guiding end-to-end customization and deployment of generative AI models in production.

You will optimize training, inference, and serving architectures across open-weight foundation models and domain-specific adaptations. The role emphasizes hands-on model customization, large-scale training/inference systems, and performance tuning on AWS chips, with