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San Francisco, California, United States
Onsite
At Bedrock, we're moving AI out of the lab and into the real world. Our team includes veterans who helped launch Waymo, scaled Segment to a $3.2B acquisition, and grew Uber Freight to $5B in revenue. Today, we're deploying autonomous systems on heavy construction equipment across the country, improving safety on job sites and accelerating schedules on critical infrastructure projects.
We're not here debating the future of AI. We're deploying it in the real world. In just two years, we've raised $350M and achieved the first fully autonomous excavator deployments in construction.
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 as fleet size grows.
Work with IT to define the data center needs for efficient data upload and the playbook to bring a new data center online for data offload purposes.
Define labor and 3rd party strategies to execute data collection. Monitor and continuously improve performance.
Team Leadership
Own data operations org design, labor strategies, and hiring and development for data technicians and couriers.
Build strong relationships with 3rd party service partners and oversee performance to specifications.
Be the bridge between active operations in the field and internal engineering teams that are customers of the data.
Build strong relationships with Customers as needed and ensure Bedrock employees and representatives comply with all active site rules and requirements.
WHAT SUCCESS LOOKS LIKE
Strong data yield per machine-hour and pipeline reliability
Lower cost per machine-hour and higher utilization.
Defined data center footprint enabling economic rapid scaling
High employee and Customer satisfaction; compliance to all Customer Site requirements
Robust Partner relationships, measured through business outcomes and performance
WHAT WE'RE LOOKING FOR
Required
8-10 years in operations, field deployment, or program leadership, including 3+ years working with distributed teams across multiple sites or regions.
Experience working with non-exempt employees and experience either directly managing non-exempt employees or overseeing contingent staff.
Track record owning operational metrics for a physical fleet at scale, including SLA design and vendor performance management.
Experience running operations for a customer-facing product against committed SLAs, or an equivalent paid-service operation.
Experience partnering with Engineering or Product as the operational voice in platform and roadmap decisions.
Comfort in an early-stage environment where the playbook is written in real time, paired with the discipline to write it down.
Strong written and verbal communication with customer executives, dealer partners, and internal leadership.
Willingness to travel approximately 30% to job sites, dealer facilities, and partner locations.
Preferred
Background in autonomy, machine control, telematics, or connected fleet solutions.
Experience operating working with a data collection fleet or equivalent field data infrastructure.
Experience structuring in-house versus third-party service decisions and the contractual and performance frameworks behind them.
Established relationships with large general contractors, hyperscaler builders, or heavy civil customers.
Understanding of data center requirements for data offload.
Experience working through a platform generation transition and/ or the introduction of new machine/equipment types.
WORKING CONDITIONS
This is a field-forward role with regular presence at active job sites, dealer and upfit facilities, and Bedrock offices. Travel is approximately 30%, concentrated during site bring-up, data center bring ups, and service partner engagements.
Bedrock Robotics is an Equal Opportunity Employer. We're committed to building a diverse and inclusive workplace. We consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, age, disability, veteran status, genetic information, or any other protected characteristic.
Reasonable Accommodations. We want our hiring process to be accessible to everyone. If you need an accommodation to participate in the application or interview process, please let your recruiter know so we can support you.
Bedrock Robotics is an Equal Opportunity Employer
We’re committed to building a diverse and inclusive workplace. We consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, age, disability, veteran status, genetic information, or any other protected characteristic.
Reasonable Accommodations
We want our hiring process to be accessible to everyone. If you need an accommodation to participate in the application or interview process, please let your recruiter know so we can support you.
