Senior AI Infrastructure Engineer

What you'll do

• Develop scalable training, orchestration, experimentation, data, and model-serving infrastructure.
• Create ML lifecycle tooling and CI/CD pipelines for profiling, evaluation, validation, and safe deployment.
• Partner with AI researchers and engineers on reusable infrastructure; mentor peers and review designs and code.

What they ask for

• 5+ years of software engineering experience building and operating production-scale ML infrastructure or distributed systems.
• Proficiency in Python, Go, or C++; strong software engineering, systems design, and concurrent programming fundamentals.
• Hands-on experience with Docker, Kubernetes, and distributed training frameworks such as PyTorch Distributed, Ray, Slurm, or Megatron-LM.
• Experience with large-scale distributed data pipelines; end-to-end project ownership; eligible to obtain and maintain an active U.S. Top Secret security clearance.

Nice to have

• Experience deploying ML infrastructure or model serving in secure, air-gapped, or regulated environments; GPU/accelerator profiling and compute optimization.
• Experience with LLM, Generative AI, or RL workloads; multi-tenant clusters or production ML observability.

Pay

$191,000 — $253,000 USD (base salary)

Tools

Python, Go, C++, Docker, Kubernetes, PyTorch Distributed, Ray, Slurm

AI focus

Infrastructure for training, evaluating, hosting, and serving LLMs, computer vision models, and RL agents, including reinforcement learning alignment loops (RLHF/DPO).