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Machine Learning Engineer: Perception Analytics

Bedrock Robotics

San Francisco, CA

ML Engineering

Posted 1 month ago

midonsite

Job Description

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 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.

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:

  • 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:

  • MSc or advanced degree in Computer Science, Robotics, or a related field

  • 4+ years of professional experience shipping perception systems to production (ideally on robotic or other embedded platforms), with strong hands-on experience in a modeling framework (e.g. PyTorch)

  • Proficient in Python and comfortable reading and writing at least one systems language (e.g. C++, Rust)

  • Hands-on experience incorporating raw sensor data (camera, lidar, IMU) into learned pipelines

  • Solid grounding in 3D geometry, sensor calibration (intrinsics/extrinsics), coordinate transforms, and camera/image re-projection algorithms

  • Strong data analysis skills across statistical characterization of sensor data, corner-case and anomaly discovery, and evaluation design

Ways to Stand Out:

One or more of the following:

  • Prior experience working with customers to understand perception data and analytics

  • Experience with the Rust programming language

  • Published work in top-tier venues such as ICRA, IROS, CVPR, ECCV, ICCV, CoRL, or RSS

Other special aspects of the role:

  • Based in the Bay Area with the ability to be onsite at our SF office on a daily/weekly basis

 

Our roles are often flexible. If you don't fit all the criteria, or are in another location (especially one where we have an office like SF or NY), please apply anyway! We'd love to consider 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.

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Career context

This role is classified as ML Engineering.

$195k - $292k is the middle 50% of disclosed salaries, measured from 82 live ML Engineering postings on this board. Roughly two thirds of postings disclose nothing, so this describes the ones that do, not the whole market.

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