Machine Learning Engineer: Perception Analytics

JOIN THE TEAM BRINGING ADVANCED AUTONOMY TO THE BUILT WORLD At Bedrock, we’re moving AI out of the lab and into the real world. Our team is composed of industry 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 machinery across the country, accelerating project schedules of billion-dollar infrastructure projects and improving safety on job sites. Backed by $350M in funding, we’re working quickly to close the gap between America's surging demand for housing, data centers, manufacturing hubs, and the construction industry's growing labor shortage. This is where algorithms meet steel-toed boots. You’ll collaborate with construction veterans and world-class engineers to solve physical-world problems that simulations can’t touch. If you're ready to apply cutting-edge technology to solve meaningful problems alongside a talented team—we'd love to have you join us. MACHINE LEARNING ENGINEER: PERCEPTION ANALYTICS We are looking for a perception engineer to build features for our customers' analytics. This isn’t just a data science job. This is developing fundamental perception features to drive customer-facing platforms. What are the real-world challenges in measuring dig productivity from lidar/camera data? Can we modify existing perception systems to provide useful metrics for job sites? How do you measure safety over an entire site given perception systems? How do you re-identify the same objects across dozens of camera views on a site several city blocks wide, through dust and changing light? WHAT YOU’LL DO: - Develop perception algorithms for re-id of vehicles on massive construction sites - Extend, modify and adapt existing perception signals for analytics needs - Work with customers to define and scope what is possible with advanced perception systems on-site - Deploy models and analytics directly to fleets of machines WHAT WE'RE LOOKING FOR: