Hybrid ML Infra Engineer for Scalable LLM Training

Harnham; United States; Hybrid; USD 180,000 - 240,000; Full time

Job summary

Harnham is partnering with an early-stage AI lab to recruit a senior ML infrastructure engineer. You will scale workloads across large GPU clusters and work on reducing training time and costs while building robust tooling used by researchers.

You will join a small, senior team with strong ownership from first build to production, and enjoy hybrid options in San Francisco or New York, with remote consideration for the right candidate.

Qualifications

• 5+ years building ML systems in production.
• Distributed training or large-scale ML infrastructure experience.
• Proven track record shipping infrastructure used by other teams.
• Python, plus PyTorch or JAX.

Responsibilities

• Scale workloads across large GPU clusters.
• Cut the time and cost of training and running models.
• Monitor and debug for large training runs.
• Evaluation tooling for large language models.

Skills

Distributed ML systems

Python

PyTorch or JAX

Production deployment

Education

Master’s or PhD in ML/CS

Job description

Harnham is partnering with an early-stage AI lab to recruit a senior ML infrastructure engineer. You will scale workloads across large GPU clusters and work on reducing training time and costs while building robust tooling used by researchers.

You will join a small, senior team with strong ownership from first build to production, and enjoy hybrid options in San Francisco or New York, with remote consideration for the right candidate.