Verification & Validation Engineer Multimodal AI

You are viewing a preview of this job. Log in or register to view more details about this job. Verification & Validation Engineer — Multimodal AI Verification & Validation Engineer — Multimodal AI Position: Verification & Validation Engineer — Multimodal AI Location: Sunnyvale, CA (Onsite) Salary: $115K–$170K Vendor Fee: $6,000 one-time fee, paid after 90 days of employment Experience: 6–12 Years Duration: 12 Months Keywords: Image Quality (IQ), Camera Validation, Camera Characterization, Python (OpenCV, NumPy), ADB / Device Control, Device Bring-Up and Flashing Note: Prioritize candidates from companies that manufacture wearable, hearable, or consumer electronics products. Job Description We are seeking a Systems Validation Engineer to own multi-sensor (e.g., vision/audio) system validation for next-generation wearables. The core of the role is building test capability that does not yet exist, especially for hardware image quality that feeds on-device AI features. A significant part of the job involves characterizing camera hardware performance in ways that predict whether AI features will work, then building the setups, methods, and automation to measure it. Established image-quality expertise is essential, applied through targeted studies and cross-functional optimization rather than routine metric-by-metric validation. Key Responsibilities Design and build validation methods for performance across vision and other sensing AI use cases, establishing operating distances, environmental conditions, scene types, and hardware limitations. Build and maintain optical lab test setups, controlled lighting scenarios, test targets, charts, opto-mechanical fixtures, and motion rigs. Develop Python automation for device control, data capture, batch gesture, audio, image and video analysis, metric extraction, and automated reporting. Establish measurement methods, pass/fail criteria, and appropriate sample sizes when requirements are not fully defined. Investigate and troubleshoot capture issues on pre-production hardware and provide actionable reports to hardware and software teams. Validate multi-camera performance and sensor interactions under environmental and system stress, including temperature, ambient brightness, thermal limitations, and power constraints. Execute system-level camera validation across photo, video, and streaming capture. Apply objective image-quality metrics, including MTF, through targeted Design of Experiments (DOE) and cross-functional optimization. Document validation methods and results to ensure repeatability and accuracy. Required Qualifications Master’s degree in Imaging Science, Computer Science, Image Processing, Computer Vision, Optics, Electrical Engineering, or a related field. 6–10 years of relevant industry experience in ISP, Computer Vision, or Image Quality Testing. Hands-on experience validating consumer imaging systems using objective image-quality metrics. Knowledge of industry image-quality protocols, test charts, and evaluation tools. Understanding of how vision AI features use camera output, including accuracy, false detections, and performance degradation. Strong Python programming experience, including building test automation and image/video analysis tools. Experience with OpenCV and NumPy. Hands-on optical lab experience, including alignment, calibration, controlled illumination, optical targets, and motion-control components. Experience working with pre-production hardware, including device bring-up, flashing, shell scripting, log capture, and automated data acquisition. Knowledge of camera geometric calibration, intrinsic/distortion calibration, and image dewarping using OpenCV. Familiarity with camera–IMU and cross-sensor temporal synchronization. Strong analytical, troubleshooting, documentation, and communication skills. Ability to work with incomplete specifications, changing priorities, and cross-functional teams. Preferred Qualifications Experience validating camera-based perception or AI features on embedded or wearable devices. Understanding of the imaging pipeline, including sensors, optics, ISP, and downstream image processing. Experience developing ground-truth datasets and applying statistical confidence measures. Exposure to SLAM, visual-inertial localization (6DoF), gaze/eye-tracking, or hand-tracking. Experience with geometric accuracy, calibration, and human-subject testing. Knowledge of subjective and perceptual image-quality evaluation. Familiarity with image sensor and optical hardware development. Experience creating custom imaging test targets, scene setups, and device-interface fixtures. Basic knowledge of optical simulation or mechanical CAD tools for test‑rig design. Candidate Sourcing Preference Prioritize candidates with experience in: Wearable and hearable consumer electronics Camera hardware validation and characterization Image Quality (IQ) testing Embedded vision and AI-enabled devices Python-based camera testing and automation Pre-production device bring-up and flashing #J-18808-Ljbffr