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Bedrock Robotics

Camera Pipeline and Image Quality Engineer

San Francisco, CA (Remote)fulltimemidAdded today

About this role

Bedrock is seeking a senior camera pipeline and image quality engineer to own the complete camera system for autonomous construction equipment, from embedded drivers through ISP tuning. You'll optimize imaging across extreme lighting conditions—full sun to darkness with dust and glare—to support both machine learning perception and remote operation on rugged job sites.

What you'll do

  • Own end-to-end camera pipeline: diagnose image quality failures, tune ISP parameters, and validate performance across full lighting range from daylight to night
  • Develop and integrate embedded camera drivers with register-level control, frame synchronization, and runtime ISP parameter exposure to autonomy stack
  • Characterize ISP pipeline behavior using parameter-level access, histogram analysis, and raw frame comparison to identify root causes of failures
  • Tune ISP and imager settings (exposure, white balance, HDR ratios, tone mapping, noise reduction) optimized for ML models and remote teleoperation
  • Establish test protocols confirming ISP changes improve low-light performance without degrading daytime model performance
  • Collaborate with perception and autonomy teams to translate scene constraints into concrete ISP tuning targets

What they're looking for

  • ISP pipeline tuning (auto-exposure, white balance, tone mapping, HDR fusion, noise reduction)
  • Embedded camera driver development (V4L2, MIPI CSI-2, GMSL, I2C)
  • Camera data pipelines on embedded platforms (frame sync, timestamping, compression, ROS2 integration)
  • Camera sensor fundamentals (CMOS architecture, shutter types, dynamic range, binning)
  • Radiometry and photon budget modeling
  • Data analysis and statistical characterization of system behavior
  • Machine learning perception pipeline validation
  • Lab and field debugging across diverse lighting conditions
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Bedrock Robotics

Bedrock Robotics develops autonomous construction machinery powered by AI and robotics technology. The company is hiring for roles spanning developer infrastructure, simulation systems, hardware engineering, field robotics application, and frontend engineering to support the development and deployment of autonomous excavators and heavy equipment.

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Likely interview questions

  • Describe your most complex ISP tuning challenge in extreme lighting and how you diagnosed and resolved exposure or tone mapping failures.
  • Walk us through your experience writing or integrating embedded camera drivers—what interfaces did you expose to the autonomy stack and why?
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