The RoleSpecter is hiring a hands-on CV/ML camera test engineer to measure how camera and optics choices affect the performance of our AI models. Working with our Optics & Camera Engineering Lead, this individual will turn experiment plans into lab and field setups, run the campaigns, push the data through our CV/ML models and report what changed and why. The work is scientific at its core: reason from first principles about optics, sensor physics and illumination, form a hypothesis, design a controlled experiment to test it, and let the data decide. This individual will collaborate with camera, CV/ML, software, hardware and field teams to put data behind every camera decision.
Responsibilities:- Form testable hypotheses from first principles (optics, sensor physics, radiometry and illumination), and design controlled experiments with defined variables, controls, sample sizes and success criteria before collecting data.
- Execute experiments comparing sensors, lenses, ISP settings, IR illumination, focus and window conditions, and measure their effect on detection, recognition and LPR performance at range.
- Build and maintain lab and outdoor test setups, including targets at known distances, controlled lighting and low-light scenes, IR illumination and chamber runs across temperature.
- Run field data-collection campaigns across sites, times of day, lighting and weather, keeping conditions, metadata and ground truth consistent.
- Run captured video through existing CV/ML models and evaluation tools, and compute model metrics alongside image-quality measurements (MTF, SNR, distortion, pixels on target).
- Script captures, camera settings, data pipelines and analysis in Python and shell on embedded Linux devices so every run is reproducible.
- Isolate the cause of performance changes across optics, sensor, ISP, illumination and environment, using statistical analysis rather than anecdote, and write clear reports that state confidence, limitations and recommendations.
- Support camera validation (focus stability, thermal, condensation, IR range) through EVT, DVT and PVT.
Qualifications:- Comfortable working in a fast-paced environment and being scrappy.
- Bachelor's Degree in Electrical Engineering, Computer Engineering, Physics, Mechanical Engineering, Computer Science, or equivalent.
- 2+ years of experience in hardware test, validation or experimental work.
- Strong Linux command line proficiency (required), including SSH, logs, file and process management and shell scripting on embedded devices.
- Proficient in Python for scripting, data processing and analysis.
- A scientific, first-principles mindset: you reason from the physics to predict results, design controlled experiments to test those predictions, and change your mind when the data says so.
- Hands-on with test setups and lab equipment, and comfortable doing 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 trends across campaigns.
- Exceptional organization and communication skills (both written and oral).
- No CV/ML background required. You'll use our existing models and evaluation tools and learn the rest on the job.
Nice to Have- Experience with cameras, image sensors, lenses or image-quality testing (MTF, SNR, low light, IR).
- Exposure to computer vision tools (OpenCV) or ML evaluation metrics such as precision and recall.
- Experience with video tooling such as FFmpeg, GStreamer or V4L2.
- Experience with thermal chambers, reliability or production test.
- Background in physics, optics or a research lab environment.
Tool Proficiency- Linux command line and shell scripting (required).
- Python with NumPy, pandas and plotting libraries.
- Git for scripts and test procedures.
- Imatest or equivalent image-quality tools (preferred).
