Senior Camera Pipeline and Image Quality Engineer in , United States

Join the Team Bringing Advanced Autonomy to the Built WorldAt 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.We are 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. Cameras power our autonomy stack on rugged construction machines across all lighting conditions, from full sun to complete darkness, in scenes with high dynamic range, dust, glare, and unpredictable site lighting. We are looking for a senior camera pipeline and image quality engineer to own the full camera pipeline: from embedded drivers and data interfaces through ISP tuning, ensuring our cameras deliver usable imagery for both ML perception models and human teleoperation across a wide range of lighting conditions.Key QualificationsHands-on experience tuning ISP pipelines on real hardware (auto exposure, auto white balance, tone mapping, demosaicing, noise reduction, and HDR fusion) with a track record of diagnosing and correcting failure modes such as AE anchoring on bright point sources, aggressive HDR sub-frame ratio compression, and tone mapping that crushes scene content in mixed-light environmentsDeep familiarity with AE algorithm internals: histogram weighting, metering zone selection, exposure ratio control in multi-exposure HDR pipelines, and lux estimation, and how these interact with scenes containing simultaneously very bright and very dark contentHands-on experience writing or integrating embedded camera drivers (V4L2, MIPI CSI-2, GMSL, I2C) and building the tooling and software interfaces that expose ISP and imager control to an autonomy software stackFamiliarity with camera data pipelines on embedded platforms: frame synchronization, timestamping, compression, bandwidth management, and integration with autonomy middleware (ROS2 or similar)Understanding of how ISP tuning choices affect downstream ML/perception model performance, and experience validating that pipeline changes do not degrade existing model behaviorWorking knowledge of camera sensor fundamentals (CMOS architecture, shutter types, CFA patterns, dynamic range, sensitivity, and binning) sufficient to reason about how sensor choice and configuration interact with ISP behaviorWorking knowledge of radiometry sufficient to interpret photon budget models, SNR predictions, and motion-blur constraints as inputs to ISP tuning requirementsStrong data analysis skills, including experience working with large datasets, building quantitative models, and using statistical methods to characterize real-world system behavior8+ years of relevant industry experience in ISP tuning, embedded camera systems, image quality engineering, or closely related rolesResponsibilitiesOwn 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 illuminationOwn embedded camera driver development and integration: register-level control, frame synchronization, and software interfaces that expose runtime ISP parameter control to the autonomy stackCharacterize 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 scenesTune 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/teleoperationEstablish and run test protocols that confirm ISP changes improve low-light performance without adversely affecting existing daytime model performance or training data compatibilityWork closely with perception, autonomy, and sensing engineering to translate scene and platform constraints (yaw rates, lux levels, detection ranges) into concrete ISP tuning targetsDebug camera issues from sensor/ISP register state through to captured imagery, both in the lab and in the fieldDefine and drive image quality characterization methodologies (SFR/MTF, noise, dynamic range, photon transfer curves) and track performance across hardware and ISP firmware generationsManage relationships with ISP, camera module, and embedded compute vendorsEducation and ExperienceBachelor's or Master's degree in Electrical Engineering, Computer Engineering, Optical Engineering, Physics, or a related field8+ years of experience in embedded camera systems, ISP tuning, image quality engineering, or closely related roles with a strong pipeline focusDemonstrated ability to characterize, diagnose, and improve camera image quality on fielded hardwareEmbedded systems experience: comfort at the hardware/software boundary, driver-level debugging, and working with real-time constraints on embedded compute platformsComfortable working in C/C++ and/or Python for driver-level work, tooling, and test automationWays to Stand Out From the FieldExperience 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 highlightsExperience 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 contextExperience with camera systems that must simultaneously serve human viewing (teleoperation/remote assistance) and ML/perception model consumptionFamiliarity with co-designing active illumination systems (NIR/visible, pulsed/continuous) alongside ISP tuningFamiliarity with IEC 60825-1 eye safety analysis for machine-mounted illuminatorsBedrock Robotics is an Equal Opportunity EmployerWe're committed to building a diverse and inclusive workplace. We consider all qualified applicants for employment without regard to race, , , sex, , gender , , ancestry, , disability, veteran status, genetic information, or any other protected characteristic.Reasonable AccommodationsWe 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.