Role Summary
The Image Quality Engineer is the final gatekeeper of perception quality, responsible for
transforming the hardware potential of perception modules into image output that is usable,
stable, and optimized for real-world applications. This role focuses deeply on ISP and image
processing pipelines, tuning image quality across diverse scenarios such as low light, backlit
scenes, outdoor environments, high dynamic range, night vision, IR, thermal, and RGB-IR
systems.
Rather than simply adjusting image appearance, this role builds high-quality perception
inputs for downstream AI, SLAM, and recognition systems, ensuring robotic platforms can
see clearly and make accurate decisions in real-world environments.
Key Responsibilities
- Perception Image Quality Strategy & Execution
Define and execute image quality strategies for perception modules, transforming camera
hardware and ISP capabilities into stable, application-ready image output across
validation and mass production phases. - Camera IQ & ISP Tuning
Tune camera image quality parameters including AE, AWB, AF, HDR, and noise reduction
to ensure consistent and predictable performance across varying lighting conditions. - Scenario-Based & Sensor-Mode Image Optimization
Optimize image quality for low-light, backlit, outdoor, high dynamic, and night-time
scenarios, including tuning for IR, thermal, and RGB-IR imaging systems. - Image Quality Measurement, Analysis & Validation
Perform image quality measurements and analysis including MTF, SNR, distortion, and
color accuracy, establishing objective evaluation methodologies to validate tuning results
and ensure production consistency. - Cross-Functional Collaboration & System Integration Support
Collaborate closely with camera firmware, driver, AI, and robotics teams to align image
quality with downstream AI, SLAM, and perception requirements, supporting system
integration and performance validation.
Requirements
- Hands-on experience with camera IQ or ISP tuning
- Strong knowledge of image quality evaluation methodologies
- Solid understanding of imaging principles and image processing pipelines
Preferred Qualifications
- Over 3 years of R&D experience with cross-functional collaboration
- Experience with Onsemi, Sony, or OmniVision camera sensors
- Hands-on ISP tuning experience with Onsemi, Sony, Indie, or NVIDIA platforms
- Experience with mass production tuning or EOL image quality validation
- Familiarity with image quality measurement tools such as Imatest and DxO