Job description
Location: US-based (remote, supporting our San Francisco office)
Engagement type: Part-time expert consultant (a few hours per week) — not a full-time role
About Unitzero:
Unitzero is a fast-scaling robotics and embodied-AI company. We operate one of the largest robot data-collection and training operations of its kind — spanning teleoperation, large-scale demonstration data pipelines, ML training infrastructure, and real-world robot deployments — and we've grown to 140+ people and 100+ robots in a matter of months, backed by top-tier investors.
Our San Francisco office anchors our US engineering and research presence.
The Role:
We're looking for a small number of highly experienced engineering leaders to act as expert advisors to our SF office. You'll work directly with the founders and engineering team for a few hours per week, helping us make high-stakes technical decisions well and fast. This is a hands-on advisory role: we want someone who has built and led engineering at scale and can go deep with us, not just offer high-level opinions.
What You'll Do:
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Advise on core engineering and architecture decisions as we scale our platform, data pipelines, and ML/GPU infrastructure (build vs. buy, cloud vs. on-prem, system design trade-offs)
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Pressure-test our technical roadmap and help us prioritize engineering investments
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Guide engineering org design as we grow: team structure, hiring bar, processes, and tooling
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Serve as a senior sounding board for the founders and engineering leads on hard technical calls
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Occasionally review designs, plans, or code where your depth is most useful
Who You Are:
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US-based
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Currently or previously a Staff Engineer, Senior Engineer, VP of Engineering, or CTO
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Have held a senior engineering role at a company valued at$200M+
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A hands-on technical leader — you've stayed close to the code and the systems, not just the org chart
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Experienced guiding engineering strategy at fast-moving, early-stage companies
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Available for a part-time advisory engagement (a few hours per week), with responsiveness when key decisions come up
Nice to Have:
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Background in robotics, ML infrastructure, large-scale data pipelines, or AI product engineering
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Experience with GPU compute strategy (training infrastructure, cloud vs. on-prem economics)
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Experience scaling engineering teams through hypergrowth
Engagement Details:
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Part-time consulting engagement, hours flexible
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Remote, US time zones, working with our San Francisco office
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Immediate start
The posted compensation range is intentionally broad to accommodate varying levels of experience. Please submit an hourly rate that accurately reflects your background and seniority.
