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Bedrock Robotics is deploying autonomous systems on heavy construction equipment across the country. The company has raised $350M in two years and achieved the first fully autonomous excavator deployments in construction, with a team including veterans from Waymo, Segment, and Uber Freight.
You will own ongoing data collection support for the fleet, ensuring machines in the field reliably produce, retain, and deliver terabyte-scale daily data volumes. As the single-threaded owner, you will define data collection strategies and oversee execution across a rapidly scaling operation. Over the next twelve months, the company will scale machine count, partners, sites, and add new machine types and a next-generation platform.
Key responsibilities include:
- Own data collection support for the fleet, ensuring reliable production and delivery of terabyte-scale daily data volumes that Engineering depends on.
- Manage field operations across Autonomous, Bedrock Intelligence, and Data Collection machines, maintaining higher monitoring frequency and faster response times for customer-facing products.
- Own data yield as a first-class operational metric alongside machine uptime, working with engineering and product to close data loss gaps in the pipeline.
- Build an economic service by ensuring clear SLAs, understanding costs, and running simulations to optimize network strategy and SLA trade-offs.
- Own field-side reliability of the data pipeline offload, connectivity, storage, and handoff, with operating cadence to catch degradation before downstream discovery.
- Translate Engineering, ML, and 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 roadmap for reducing manual effort as fleet grows.
- Work with IT to define data center needs for efficient data upload and playbook for bringing new data centers online.
- Define labor and third-party strategies for data collection execution, monitoring, and continuous improvement.
- Own data operations org design, labor strategies, hiring, and development for data technicians and couriers.
- Build strong relationships with third-party service partners and oversee performance to specifications.
- Serve as bridge between field operations and internal engineering teams.
- Build customer relationships and ensure compliance with site requirements.
Success is measured by strong data yield per machine-hour, pipeline reliability, lower cost per machine-hour, higher utilization, defined data center footprint for economic scaling, high employee and customer satisfaction, compliance to site requirements, and robust partner relationships.
This is a field-forward leadership 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.
REQUIREMENTS:
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 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 equivalent paid-service operation
- Experience partnering with Engineering or Product as the operational voice in platform and roadmap decisions
- Comfort in early-stage environment where playbook is written in real time, paired with discipline to document it
- 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 a data collection fleet or equivalent field data infrastructure
- Experience structuring in-house versus third-party service decisions and contractual/performance frameworks
- Established relationships with large general contractors, hyperscaler builders, or heavy civil customers
- Understanding of data center requirements for data offload
- Experience working through platform generation transition and/or introduction of new machine/equipment types
