Head of Engineering, Platform

What you'll do

• Convert research into scalable tools and oversee infrastructure for interpretability, training, and inference.
• Recruit, hire, and retain machine learning engineers and build a high-performing engineering team.
• Drive platform adoption and work directly with customers and go-to-market teams.

What they ask for

• 10+ years of engineering experience, including 5+ years in engineering leadership roles.
• Proven success scaling engineering teams at high-growth startups or frontier AI labs, plus a strong track record recruiting machine learning engineers from top AI organizations.
• Deep expertise in ML infrastructure, distributed systems, and large-scale model training; hands-on proficiency with PyTorch or JAX, modern ML tooling, and inference engines.
• Strong AI/ML community network and genuine passion for AI safety, interpretability, and building trustworthy systems.

Nice to have

• Experience at a frontier AI lab or leading AI research organization; experience shipping ML products to enterprise or research customers.
• Familiarity with interpretability, alignment, or AI safety research; public presence through publications, open-source contributions, or speaking engagements.

Pay

$300,000 - $450,000 USD (base salary)

Tools

PyTorch, JAX

AI focus

Leads development of AI interpretability infrastructure and tools, including model training and inference at frontier scale.