Senior Camera Pipeline and Image Quality Engineer

Responsibilities

• Own the camera pipeline end to end: diagnose image quality failures, tune ISP parameters, and validate improvements across the full operating radiometric range from bright daylight to night with machine-mounted illumination
• Own embedded camera driver development and integration: register-level control, frame synchronization, and software interfaces that expose runtime ISP parameter control to the autonomy stack
• Characterize existing ISP pipeline behavior from first principles: identify root causes of image quality failures using parameter-level access, histogram analysis, raw vs processed frame comparison, and controlled test scenes
• Tune ISP and imager settings (exposure, white balance, HDR sub-frame ratios, tone mapping, noise reduction) to optimize image quality for both ML perception models and remote assistance/teleoperation
• Establish and run test protocols that confirm ISP changes improve low-light performance without adversely affecting existing daytime model performance or training data compatibility
• Work closely with perception, autonomy, and sensing engineering to translate scene and platform constraints (yaw rates, lux levels, detection ranges) into concrete ISP tuning targets
• Debug camera issues from sensor/ISP register state through to captured imagery, both in the lab and in the field
• Define and drive image quality characterization methodologies (SFR/MTF, noise, dynamic range, photon transfer curves) and track performance across hardware and ISP firmware generations
• Manage relationships with ISP, camera module, and embedded compute vendors
• Education and Experience
• Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, Optical Engineering, Physics, or a related field
• 8+ years of experience in embedded camera systems, ISP tuning, image quality engineering, or closely related roles with a strong pipeline focus
• Demonstrated ability to characterize, diagnose, and improve camera image quality on fielded hardware
• Embedded systems experience: comfort at the hardware/software boundary, driver-level debugging, and working with real-time constraints on embedded compute platforms
• Comfortable working in C/C++ and/or Python for driver-level work, tooling, and test automation
• Ways to Stand Out From the Field
• Experience diagnosing and correcting AE anchoring and HDR tone mapping failures in scenes with extreme intra-frame contrast: retroreflective surfaces, direct artificial light sources, or simultaneous deep shadow and bright highlights
• Experience with construction, off-road, automotive, or other outdoor autonomous/robotic platforms operating in harsh environments (dust, vibration, wide temperature range, direct sunlight and full dark)
• Experience with automotive-grade high-speed camera interfaces (GMSL, FPD-Link, MIPI CSI-2) and embedded compute platforms (e.g. Nvidia Jetson/Orin) in a production or near-production deployment context
• Experience with camera systems that must simultaneously serve human viewing (teleoperation/remote assistance) and ML/perception model consumption
• Familiarity with co-designing active illumination systems (NIR/visible, pulsed/continuous) alongside ISP tuning
• Familiarity with IEC 60825-1 eye safety analysis for machine-mounted illuminators
• 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.