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System Validation Engineer (Multimodal AI / Camera) || Sunnyvale,California (Onsite)
Stellent IT LLCSunnyvale, CA🇺🇸United StatesPosted 19 Aug 2026
Quick Overview
Work Type
On Site
Level
Mid Senior
Job Description
Hi,
Position: System Validation Engineer (Multimodal AI / Camera)
Location: Sunnyvale, California (Onsite)
Duration: Full Time
Interview Mode: Video
JD
What you will do
- Plan and execute system-level camera validation across photo, video and streaming capture, covering the full range of objective image quality and capture performance metrics.
- Design and build validation methods for camera hardware performance across vision AI use cases such as object recognition, text reading and code recognition - establishing the distances, lighting conditions and scene types over which the hardware supports each feature, and characterizing where and how it fails.
- Build and own the test capability itself: specify and assemble lab setups, controlled lighting scenarios, test targets and charts, opto-mechanical fixtures and motion rigs, and keep them calibrated, documented and repeatable.
- Develop Python automation to take testing from one-off manual measurements to high-volume, repeatable runs - device control and data capture, batch image and video analysis, metric extraction and automated reporting.
- Where a requirement or limit is still open, propose the measurement method, the pass/fail approach, and the data volume needed to make the result credible.
- Investigate and root-cause image quality and capture issues on pre-production hardware, and produce clear, actionable reports for hardware and software teams, with sound judgment on the conclusions and step forward.
- Validate camera performance under environmental and system stress, including temperature, ambient brightness extremes and thermally or power-constrained operation.
- Document methods and results so that tests can be repeated and results defended by others.
Minimum qualifications
- Degree in Imaging Science, Optics, Electrical Engineering, Computer Science, Image Processing or a related field, with substantial relevant industry experience in ISP or camera validation.
- Demonstrated hands-on experience validating consumer camera systems against objective image quality metrics, with working knowledge of industry image quality test protocols, charts and evaluation tools.
- Practical understanding of how vision AI features consume camera output - enough to design tests that expose camera-side limitations, and to reason about accuracy, false detections, and the conditions under which a feature degrades. Model development experience is not required.
- Strong Python, with demonstrated experience building test automation and image or video analysis tooling, not only running existing scripts.
- Hands-on optical lab capability: creating, aligning, calibrating and maintaining sensitive measurement setups, working with controlled illumination, targets, opto-mechanics and motion control components.
- Comfortable working on pre-production hardware: device bring-up, flashing, shell scripting, log capture and scripted data acquisition.
- Strong analytical judgement and clear reporting. You can explain a measurement, and defend it or revisit it and drive towards clarity when your result is challenged.
- Able to work with ambiguity, incomplete specifications and shifting priorities, and to juggle competing requests from a large cross-functional team.
Preferred qualifications
- Experience validating camera-driven perception or AI features on an embedded or wearable device.
- Understanding of system-level interactions across the imaging pipeline - sensor, optics, ISP, and the downstream consumers of image data.
- Experience building ground-truth test sets and reasoning about sample size and statistical confidence in validation results.
- Exposure to gaze or eye-tracking, or hand-tracking, validation - including test design involving human subjects and inter-subject variability.
- Experience with subjective and perceptual image quality evaluation alongside objective metrics.
- Familiarity with image sensor and optics hardware development and the associated evaluation methodologies.
- Prototyping skill with imaging test targets, custom scene setups and device interface fixtures.
Basic familiarity with optical simulation or mechanical CAD tools for designing test rigs
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Skills
Shell
CAD
Python
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