Forward Deployed Engineer

About the company

Our client is a Series A, revenue-generating Bay Area company that supplies robot training data — teleoperation, on-embodiment and egocentric — to frontier AI labs and humanoid robotics companies, alongside its own hardware and a model fine-tuning loop. The team is around twenty people, it was founded in 2023, and the founders are robotics PhDs who previously worked at a well-known robotics AI company. They describe revenue as strong and stable, and say they currently have more customers than they can serve.

The role

This is the first forward deployed engineering hire, and today the founders are doing the job themselves. You own end-to-end data delivery for strategic customers: you understand the pipeline, you guarantee data quality, you scope what the customer actually needs, you run QA before anything ships, and you clear your own blockers. You are also the first technical responder for your accounts, triaging questions, resolving most problems without escalating, and managing timeline expectations with sophisticated robotics and AI buyers. It is a genuinely hybrid seat, and the client was explicit that if forced to choose between the technical side and the communication side, the technical side wins: traditional sales or solutions engineers who need another engineer to work out the answer are not what this role is. There is no outbound selling — the customer list already exists and the problem is serving it well.

What you'll do

• Own end-to-end data delivery for strategic customers — understand the pipeline, ensure data quality, scope requirements, run QA before shipping, and clear blockers yourself
• Be the first technical responder for your accounts — triage customer questions, resolve most problems without escalating to other engineers, and manage timeline expectations
• Write production code against the data pipeline rather than handing problems to another team
• Represent the company's technical depth to sophisticated robotics and AI customers, in language that is easy to follow
• Turn recurring customer needs and delivery pain points into product and pipeline improvements, and into reusable playbooks
• Grow the forward-deployed motion over time — later leading platform-integration engagements and model fine-tuning and evaluation services for enterprise customers

Nice to have

• Has worked at a highly technical, enterprise or S-tier company — the client names Palantir, Snowflake, Scale AI and Databricks as references rather than as a requirement, and actively wants candidates from outside that list too
• Founding engineer or startup founder experience — the client treats this as a real plus for the comfort with ambiguity and the agency it builds
• Experience in robotics or embodied AI (a plus only, never required)
• Has worked with data pipelines, data quality or data delivery at scale
• A degree from a strong technical school

Tech stack

Python and data pipelines, with robotics and AI/ML throughout; robotics data formats including MCAP and HDF5; data quality, QA and evaluation tooling, plus model fine-tuning and evaluation work for enterprise customers.

Compensation & logistics

• $230k–$310k base plus competitive equity, and the client has said comp is negotiable for very strong candidates
• On-site in San Mateo, CA five days a week; relocation is not supported, so you need to be in the Bay Area already
• Two hires on this role
• Open to candidates who need no sponsorship and to visa transfers such as OPT and H-1B; the client will not file a new, first-time visa sponsorship
• Interview process: a 30-minute hiring manager introduction, a 60-minute problem-solving and coding round, a 60-minute system design round covering data pipelines and infrastructure, then a one-day on-site in San Mateo
• The team is hiring mostly from inbound applicants today, with a few candidates in middle stages and none late-stage
• Full-time