CV/ML Camera Test Engineer

Specter • San Francisco, CA

1d

About The Position

Specter is hiring a hands-on CV/ML Camera Test Engineer to measure how camera and optics choices affect the performance of its AI models. Working with the Optics & Camera Engineering Lead, the engineer will translate experiment plans into laboratory and field setups, conduct test campaigns, evaluate captured data using existing CV/ML models, and report what changed and why. The work applies first-principles reasoning about optics, sensor physics, and illumination to form hypotheses, design controlled experiments, and draw conclusions from data.

The role collaborates with camera, CV/ML, software, hardware, and field teams to provide evidence for camera decisions. It includes laboratory and outdoor testing, video analysis, reproducible scripting and data pipelines, camera validation through EVT, DVT, and PVT, and clear reporting of results, confidence, limitations, and recommendations. No CV/ML background is required; the engineer will use existing models and evaluation tools and learn the rest on the job.

Requirements

• Bachelor's degree in Electrical Engineering, Computer Engineering, Physics, Mechanical Engineering, Computer Science, or equivalent.
• At least 2 years of experience in hardware testing, validation, or experimental work.
• Strong Linux command-line proficiency, including SSH, logs, file and process management, and shell scripting on embedded devices.
• Proficiency in Python for scripting, data processing, and analysis.
• Scientific, first-principles mindset: reason from physics, design controlled experiments, and revise conclusions in response to data.
• Hands-on experience with test setups and laboratory equipment; comfortable with outdoor field work, including at night and in bad weather.
• Strong grounding in statistics and experimental design, including hypothesis testing, confidence intervals, variance, sample sizing, and identifying trends across campaigns.
• Exceptional written and oral organization and communication skills.
• Comfort working in a fast-paced environment and taking a scrappy, resourceful approach.

Nice To Haves

• Experience with cameras, image sensors, lenses, or image-quality testing, including MTF, SNR, low light, or IR.
• Exposure to computer vision tools such as OpenCV or ML evaluation metrics such as precision and recall.
• Experience with video tools such as FFmpeg, GStreamer, or V4L2.
• Experience with thermal chambers, reliability testing, or production testing.
• Background in physics, optics, or a research laboratory environment.
• Python experience with NumPy, pandas, and plotting libraries.
• Git experience for scripts and test procedures.
• Experience with Imatest or equivalent image-quality tools.

Responsibilities

• Form testable hypotheses based on optics, sensor physics, radiometry, and illumination; design controlled experiments with defined variables, controls, sample sizes, and success criteria.
• Conduct experiments comparing sensors, lenses, ISP settings, IR illumination, focus, and window conditions, and measure effects on detection, recognition, and LPR performance at range.
• Build and maintain laboratory and outdoor test setups, including known-distance targets, controlled lighting, low-light scenes, IR illumination, and temperature-chamber runs.
• Run field data-collection campaigns across sites, times of day, lighting conditions, and weather while keeping conditions, metadata, and ground truth consistent.
• Run captured video through existing CV/ML models and evaluation tools; calculate model metrics alongside image-quality measurements such as MTF, SNR, distortion, and pixels on target.
• Script captures, camera settings, data pipelines, and analysis in Python and shell on embedded Linux devices to make test runs reproducible.
• Use statistical analysis to isolate performance changes across optics, sensor, ISP, illumination, and environment; write clear reports stating confidence, limitations, and recommendations.
• Support camera validation, including focus stability, thermal performance, condensation, and IR range, through EVT, DVT, and PVT.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level