Machine Learning Engineer: Robotics ML Generalist

Overview

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 $80M 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.

Bedrock is bringing autonomy to the construction industry! We’re a group of veterans from the autonomous vehicle industry who are passionate about bringing the benefits of automation to areas in the construction industry currently underserved by the market.

• Develop and optimize real-time ML models for edge deployment on robotic systems
• Work with vendors to label data and build robust data extraction and labeling pipelines
• Design custom metrics to evaluate model performance in the field
• Reduce model latency using tools like ONNX, Tensor
  
  RT, or similar

• Practical experience applying machine learning with deep learning frameworks, such as PyTorch, to solve real-world problems
• Proficiency in Python and comfort with at least one systems language (e.g., C++, Rust)
• Experience deploying ML models to robotic systems or other physical platforms
• Experience incorporating raw sensor data like camera, lidar, radar, IMUs, etc into deep learning algorithms.
• Bonus:
  Practical application of incorporating 3D geometry into deep learning models
• Bonus:
  Published work in conferences such as ICRA, IROS, CoRL, CVPR, ECCV, ICCV, ICML, NeurIPS
• We’re especially interested in engineers who thrive at the intersection of ML research and real-world robotics applications.

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.