Member of Technical Staff, Infrastructure

About the Role

This is a hands-on infrastructure engineering role at an early-stage robotics company, sitting at the intersection of distributed systems, ML infrastructure, and deployed robot fleets. You will own critical systems end-to-end, from petabyte-scale data pipelines to GPU cluster orchestration, and your decisions will shape the engineering foundation while the codebase is still young enough for them to matter.

What You'll Do

• Build and own distributed systems for training orchestration, compute scheduling, fault tolerance, and large-scale model training networking.
• Design data pipelines that ingest petabytes of robot fleet telemetry and video corpora, keeping GPUs fed without stalls.
• Architect a continuous-learning loop that moves production trajectories from deployed robots back into training reliably and autonomously.
• Go wherever the bottleneck is week to week, whether that is a deployment path, a core library, or an observability gap.
• Build internal tooling that compounds over time and makes every engineer and researcher on the team faster.

What We're Looking For

• 3+ years of experience in systems engineering, ML infrastructure, or distributed systems, ideally at a well-regarded tech company or research lab.
• Strong systems engineering fundamentals: proven experience building or maintaining distributed systems, data pipelines, or GPU and compute infrastructure.
• Hands-on experience shipping software on physically deployed robots or autonomous vehicles in production.
• Proficiency in Python and C/C++.
• Experience with petabyte-scale data systems or multi-node training orchestration is a strong plus.
• Background in ML infrastructure or large-scale training infrastructure projects is a strong plus.
• Must be available to work on-site six days per week in San Francisco.

Compensation & Benefits

Base salary: $200,000 to $350,000 USD annually. Visa sponsorship is not available for this role.

Location

On-site in San Francisco, California, United States. This role requires in-person attendance six days per week.