Data Operations Lead at Bedrock Robotics in San Francisco, CA

Job description

Join the team bringing autonomy to the built world At Bedrock, we're moving AI out of the lab and onto real job sites. Our team includes veterans who helped launch Waymo, scaled Segment to a $3.2B acquisition, and grew Uber Freight to $5B in revenue. We retrofit the heavy equipment contractors already own, starting with excavators, so experienced crews can safely take on more projects and deliver more of the critical infrastructure our society needs. In August 2026, Bedrock-equipped excavators began doing fully autonomous, paid work on live commercial job sites. We've more than doubled our customer base since 2025, and our machines now work with contractors across the South, Midwest, and Mid-Atlantic In October 2026, we raised a $600M Series C co-led by CapitalG and Emergence Capital, bringing our total funding to nearly $1B. We're using it to put more autonomous machines to work, build the field and operations teams behind every deployment, and expand into new machine types and job-site tasks. This is where algorithms meet steel-toed boots. You'll work alongside construction veterans and world-class engineers to solve physical-world problems that simulations can't touch. If you're ready to do meaningful work on hard problems, we'd love to have you join us. ABOUT THE ROLE We are seeking a Data Operations Lead to own ongoing data collection support for the fleet - ensuring machines in the field reliably produce, retain, and deliver terabyte-scale daily data volumes. Over the next twelve months, we will rapidly scale our machine count, partners and sites while also adding net-new machine types and a next-generation platform. You will be the single-threaded owner to define our data collection strategies as well as oversee execution. You will help define how the data is collected, when the data is collected, and the data center strategy for supporting efficient upload. You will provide the critical data our Engineering teams rely on, including helping to define service level agreements and methods, monitoring, and infrastructure needs. This is a field-forward leadership role. You will build the organization and the systems that keep data flowing, ensuring our engineering team has what they need in an efficient and economic method. WHAT YOU'LL DO Own ongoing data collection support for the fleet ensuring machines in the field reliably produce, retain, and deliver the terabyte-scale daily data volumes Engineering depends on. Own field operations across Autonomous and Bedrock Intelligence machines at customer and engineering product standards: higher monitoring frequency, faster response, and stricter data completeness than the data collection fleet, because customers are paying for and acting on what these machines produce. Own field operations across Data Collection machines at engineering product standards: define efficient means of data collection that still enable engineers with the critical data they need to mature our models. Own data yield as a first-class operational metric alongside machine uptime: what percentage of operating hours produce usable, complete, correctly-labeled data, and what is driving the gap. Work with engineering and product to prioritize and close places where data loss happens in the pipeline. Build an overall economic service by ensuring SLAs are clear and costs understood, run simulations to better understand network strategy and SLA trade-offs and to optimize operations. Own the field-side reliability of the data pipeline offload, connectivity, storage, and handoff and the operating cadence that catches degradation before Engineering or a paying customer discovers it downstream. Translate Engineering, ML, and Bedrock Intelligence product requirements into field-executable standards, and translate field constraints back into realistic commitments. Partner with Infrastructure, Product, Engineering and Data teams on tooling, instrumentation, and the roadmap for reducing manual effort in data operations