Position: Sr. Camera Validation Engineer
Location: San Francisco, CA (USA)
Exp: 5-8 years
Key skills: Imatest, DxO Analyzer, RAW viewers, ISP, ColorChecker, light boxes, HDR charts, GStreamer, ADB, internal camera HAL tools, log analysis tools, Python (OpenCV, Pillow, NumPy), Bash/PowerShell, Jira, Confluence, test case management systems
- Own the validation of complete camera systems at the product level, ensuring that optics, sensors, ISP pipelines, tuning blocks, and imaging algorithms
work together to deliver highquality imaging performance. Drive endtoend sanity testing, anomaly detection, tooling integration, and largescale data management across multiple product generations.
Regards,
- Validate full camera systems including optics, sensor, ISP pipeline, tuning blocks, and imaging algorithms across device generations.
- Build and maintain productlevel sanitycheck test cases in collaboration with block owners.
- Execute endtoend ISP pipeline validation, regression testing, and feature verification.
- Compare results against golden references from previous generations to identify anomalies and regressions.
- Perform root cause analysis across hardware, firmware, and software imaging components.
- Conduct structured camera testing in image labs and realworld environments (HDR, lowlight, motion, portrait, indoor/outdoor).
- Capture, tag, and maintain largescale image and video datasets for tuning, validation, and ML training.
- Participate as a portrait subject when needed for camera tests and database capture.
- Organize test results, maintain metadata, and manage the lifecycle of the image database.
- Develop lightweight automation scripts to streamline test execution, data processing, and reporting.
- Integrate validation workflows with internal tooling such as GStreamer pipelines, Jira ticketing systems, and automated test runners.
- File, track, and manage issues through Jira, ensuring clear communication with crossfunctional teams.
Collaborate with imaging engineers, algorithm developers, hardware teams, and QA to drive productlevel quality.
5 to 8 years of experience
- Deep understanding of camera imaging systems: optics, sensors, ISP, tuning, and imagequality fundamentals.
- Strong experience with productlevel camera testing and imagequality evaluation.
- Proficiency with GStreamer for camera pipeline testing, streaming, and debugging.
- Experience using Jira for bug tracking, workflow management, and validation dashboards.
- Strong scripting skills in Python or Bash for automation and data processing.
Familiarity with OpenCV, NumPy, and imageprocessing libraries.
- Experience with image capture tools, lab equipment, and controlled lighting environments.
- Ability to perform crossblock root cause analysis and communicate findings clearly.
Strong organizational skills for managing largescale image datasets..
Preferred Tools & Technologies:
- Imatest, DxO Analyzer, Image Engineering tools
- RAW viewers, ISP tuning tools, sensor evaluation tools
- ColorChecker, light boxes, HDR charts
- GStreamer, ADB, internal camera HAL tools, log analysis tools
- Python (OpenCV, Pillow, NumPy), Bash/PowerShell
Jira, Confluence, test case management systems
Master's and Ph.D. in Electrical Engineering, Computer Science, Computer Engineering
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