Staff AI Infrastructure Engineer

What you'll do

• Build training, orchestration, experimentation, and automated evaluation infrastructure; improve research workflows and remove bottlenecks.
• Develop large-scale multimodal data pipelines and low-latency model serving, including ML CI/CD for cloud and air-gapped edge environments.
• Set platform technical direction, collaborate across research and engineering teams, and help recruit, mentor, and grow the infrastructure team.

What they ask for

• 7+ years of software engineering experience building and operating production-scale machine-learning systems and platforms.
• Proficiency in Python, Go, C++, or similar backend languages; deep understanding of ML systems design, memory management, and distributed computing.
• Experience with Docker, Kubernetes, GPU scheduling/orchestration, distributed training frameworks, and distributed ETL pipelines for large datasets.
• Experience setting technical direction, leading complex migrations, and mentoring senior engineers; eligible to obtain and maintain an active U.S. Top Secret security clearance.

Nice to have

• Experience with ML infrastructure in secure or air-gapped environments, or with LLM, Generative AI, or RL training and evaluation platforms.
• Experience with AI accelerators beyond standard GPUs, multi-tenant ML platforms, hardware performance optimization, or ML observability.

Pay

$220,000 — $292,000 USD (base salary)

Tools

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

AI focus

Builds infrastructure for training, evaluating, hosting, and serving AI models, including LLMs, computer vision, and reinforcement-learning agents; includes RLHF/DPO alignment and model safety evaluation.