ML Systems Engineer

Highlights

• Build agentic infrastructure for large-scale training and reinforcement learning.
• Develop high-performance inference and serving systems at scale.
• Accelerate scientific breakthroughs across materials, energy and beyond.

What they offer

• Equity

Ideal candidate

High-ownership systems builder who thrives on complex end-to-end problems and moves fast. Passionate about pushing AI systems frontiers and accelerating scientific discovery with AI agents.

Requirements

• Strong systems programming and performance engineering skills
• Experience building high-performance ML infrastructure at scale
• Ability to own complex technical problems end-to-end
• Strong coding ability and engineering judgment, including working effectively with AI agents
• High ownership, fast execution and passion for pushing AI systems and scientific discovery
• Bachelor's degree or similar experience
• Deep expertise in at least one: training, distributed runtime, inference, sandboxing, GPU kernels, or GPU communication