---
title: 'Senior Camera Pipeline and Image Quality Engineer at Bedrock Robotics Inc'
canonical: 'https://feeny.ai/job/senior-camera-pipeline-and-image-quality-engineer-bedrock-robotics-inc-san-a5g8v8zc5ekr'
type: 'job'
last_seen: '2026-09-12'
---

# Senior Camera Pipeline and Image Quality Engineer at Bedrock Robotics Inc

- **Company:** Bedrock Robotics Inc
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-07-29
- **Last confirmed live:** 2026-09-12
- **Apply:** https://jobs.ashbyhq.com/bedrock-robotics/63a38fa3-cb64-4104-8f06-d5036c8b315c

## Job description

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 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 Qualifications

- Hands-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 environments
- Deep 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 content
- Hands-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 stack
- Familiarity 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 behavior
- Working 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 behavior
- Working knowledge of radiometry sufficient to interpret photon budget models, SNR predictions, and motion-blur constraints as inputs to ISP tuning requirements
- Strong data analysis skills, including experience working with large datasets, building quantitative models, and using statistical methods to characterize real-world system behavior
- 8+ years of relevant industry experience in ISP tuning, embedded camera systems, image quality engineering, or closely related roles

## 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.

## About Bedrock Robotics Inc

## Company Overview
- **One-liner**: Bedrock Robotics brings advanced autonomy to heavy machinery, upgrading existing construction equipment for fully autonomous operation to help the industry build faster and safer.
- **Entity Type**: Private (Series B)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2024
- **Founders**: Boris Sofman (Co-Founder & CEO), Kevin Peterson (Co-Founder & CTO), Tom Eliaz (Co-Founder & VP, Engineering), Laurent Hautefeuille (Co-Founder & VP, Engineering)

## Core Business
- **Primary industry**: Robotics Engineering / Autonomous Heavy Equipment / Construction Technology
- **Target customers**: B2B — construction companies, infrastructure developers, and heavy machinery fleet operators
- **Mission or purpose**: Transforming how we develop the world by enabling the construction industry to build at the pace of societal demand through autonomous technology.

## Products & Services
- **[Bedrock Operator]**: An autonomous system that retrofits existing heavy equipment (e.g., excavators) to operate independently, adapting to on-site challenges, tracking productivity, and delivering expert-level quality with superhuman safety. Type: Hardware + Software (Autonomy Platform).

## Market Standing
- **Valuation**: Not publicly disclosed (latest funding round values the company at a significant premium).
- **Key Metric**: Total Funding — $350M raised (Series B of $270M closed in early 2026).
- **Notable Investors/Partners**: NVentures (NVIDIA), Valor Equity Partners, 8VC, Eclipse, Tishman Speyer, and 21+ other investors. Backed by key strategic partners in construction and real estate.
- **Growth Signals**: 
    - Headcount grew 5,950% YoY (from ~1 to 85 employees in its first year).
    - Named "Outperformer" among 15 companies including Caterpillar, Sandvik, and Epiroc by CB Insights.
    - Covered by The New York Times, Forbes, and Engineering News Record for major funding and field deployments.
    - Completed a major project removing 65,000 cubic yards of dirt on a Southwest construction site.

## Competitive Advantages
- **Deep autonomy heritage**: Founding team spent years at Waymo perfecting autonomous systems for complex, safety-critical driving on public roads — a rare and transferable expertise.
- **Real-world deployment**: Technology is proven on active construction sites (not just simulations), with tens of thousands of hours of field data.
- **Retrofit model**: Upgrades existing heavy equipment rather than requiring new machinery, lowering adoption barriers for construction firms.
- **Continuous improvement**: The Bedrock Operator learns and sharpens skills with every project, creating a data moat.

## Strategic Focus
- Scaling deployment of autonomous heavy equipment across major construction projects (housing, data centers, energy, factories).
- Expanding the range of machinery types that can be retrofitted.
- Deepening partnerships with construction firms and equipment manufacturers.
- Growing the engineering and field operations teams to accelerate product development and customer support.

## Why Work Here
- **Culture**: A passionate, product-driven team that works hand-in-hand with customers. Emphasizes real-world impact — field tests on active construction sites generate as much excitement as breakthrough code.
- **Work Environment**: Hybrid presence with offices in Downtown San Francisco, Soho (New York City), and test facilities in Texas and California.
- **Perks**: Comprehensive health & well-being coverage, daily in-office meals, commuter benefits, unlimited time off, paid parental leave, 401k retirement plan.
- **Engineering Focus**: Work on unsolved problems — bringing autonomous technology to market that will revolutionize construction. Exposure across product, technology, and business. First pair of steel-toed boots provided.
- **Team**: Collaborate with a diverse group of experts from Waymo, Zoox, Cruise, Caterpillar, and other top robotics/autonomy companies.

## Sources
1. [bedrockrobotics.com](https://bedrockrobotics.com/)
2. [bedrockrobotics.com/about](https://bedrockrobotics.com/about)
3. [bedrockrobotics.com/careers](https://bedrockrobotics.com/careers)
4. [cbinsights.com](https://www.cbinsights.com/company/bedrock-robotics)
5. [linkedin.com](https://www.linkedin.com/company/bedrock-robotics)

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