System Validation Engineer (Multimodal AI / Camera) || Sunnyvale,California (Onsite)

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