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About the Role

Join a team deploying autonomous systems on heavy construction machinery, accelerating infrastructure projects and improving job site safety. Apply cutting-edge technology to solve meaningful physical-world problems alongside construction veterans and world-class engineers.

Responsibilities

• Own the camera pipeline end to end, diagnosing image quality failures, tuning ISP parameters, and validating improvements across the full operating radiometric range.
• Own embedded camera driver development and integration, including register-level control, frame synchronization, and software interfaces for runtime ISP parameter control.
• Characterize existing ISP pipeline behavior from first principles, identifying root causes of image quality failures.
• Tune ISP and imager settings to optimize image quality for ML perception models and remote assistance/teleoperation.
• Establish and run test protocols to confirm ISP changes improve low-light performance without adversely affecting daytime model performance.
• Translate scene and platform constraints into concrete ISP tuning targets.
• Debug camera issues from sensor/ISP register state to captured imagery, in lab and field.
• Define and drive image quality characterization methodologies and track performance across hardware and ISP firmware generations.
• Manage relationships with ISP, camera module, and embedded compute vendors.

Requirements

• Hands-on experience tuning ISP pipelines on real hardware with a track record of diagnosing and correcting failure modes.
• Deep familiarity with AE algorithm internals and their interaction with challenging scenes.
• Hands-on experience writing or integrating embedded camera drivers and building associated tooling and software interfaces.
• Familiarity with camera data pipelines on embedded platforms.
• Understanding of how ISP tuning choices affect downstream ML/perception model performance.
• Working knowledge of camera sensor fundamentals.
• Working knowledge of radiometry.
• Strong data analysis skills, including experience with large datasets and statistical methods.
• 8+ years of relevant industry experience in ISP tuning, embedded camera systems, image quality engineering, or closely related roles.
• Demonstrated ability to characterize, diagnose, and improve camera image quality on fielded hardware.
• Embedded systems experience, including driver-level debugging and real-time constraints.
• Comfortable working in C/C++ and/or Python for driver-level work, tooling, and test automation.

Skills

• ISP tuning
• Embedded camera systems
• Image quality engineering
• AE algorithm internals
• Embedded camera drivers (V4L2, MIPI CSI-2, GMSL, I2C)
• Camera data pipelines on embedded platforms
• ML/perception model performance validation
• Camera sensor fundamentals
• Radiometry
• Data analysis
• C/C++
• Python
• Diagnosing AE anchoring and HDR tone mapping failures
• Construction/off-road/automotive/outdoor autonomous/robotic platforms
• Automotive-grade high-speed camera interfaces (GMSL, FPD-Link, MIPI CSI-2)
• Embedded compute platforms (Nvidia Jetson/Orin)
• Camera systems serving human viewing and ML/perception models
• Co-designing active illumination systems
• IEC 60825-1 eye safety analysis

Location

• Remote
• San Francisco, CA
• New York, NY

Work Type

• Full-time

Experience Level

• Senior
• 8+ years of relevant industry experience

Education Level

• Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, Optical Engineering, Physics, or a related field

About the Company

• Bedrock is moving AI out of the lab and into the real world, deploying autonomous systems on heavy construction machinery.
• The team includes industry veterans from Waymo, Segment, and Uber Freight.
• Backed by $350M in funding, Bedrock is addressing the construction industry's growing labor shortage.
• The company is passionate about bringing the benefits of automation to underserved areas of the construction industry.