V&V engineer - Multimodal AI

Quest Global; Sunnyvale (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Quest Global is seeking a Systems Validation Engineer to own multi-sensor (vision/audio) system validation for next-generation wearables. You will build test capabilities for HW image quality feeding on-device AI, characterize camera performance, and develop automated testing pipelines.

You will design lab setups, perform media and scene variations, and drive cross-functional optimization to ensure robust AI features across environments. Strong Python and image-quality expertise are essential.

Qualifications

• Masters degree in Imaging Science, Computer Science, Image Processing, CV, Optics or Electrical Engineering with substantial industry experience.
• Hands-on validating imaging systems against objective image quality metrics and test protocols.
• Experience designing tests to expose camera-side limitations and to reason about accuracy, false detections, and conditions of degradation.

Responsibilities

• Design and implement validation methods for vision and sensing AI use cases across hardware setups and environments.
• Build and own lab test capability, including controlled lighting, targets, fixtures, and motion rigs, with calibration and repeatability.
• Develop Python automation for automated testing, data capture, analysis, and reporting.
• Advise on measurement methods, pass/fail criteria, and data volume needed for credible results.
• Investigate pre-production hardware issues and produce clear reports for hardware/software teams.
• Validate multi-camera interactions under varying environmental conditions and power constraints.
• Plan system-level validation across photo, video, and streaming capture for AI use cases, applying objective image-quality metrics.
• Document methods and results for repeatability and defendability.

Skills

Python programming

Test automation

Image quality testing

Camera calibration knowledge

Analytical reporting

Problem solving

Education

Master's degree in Imaging Science / Computer Science / Electrical Engineering

Tools

OpenCV

Shell scripting

Lab equipment setup

Job description

Who We Are

Quest Global delivers world-class end-to-end engineering solutions by leveraging our deep industry knowledge and digital expertise. By bringing together technologies and industries, alongside the contributions of diverse individuals and their areas of expertise, we are able to solve problems better, faster. This multi-dimensional approach enables us to solve the most critical and large-scale challenges across the aerospace & defense, automotive, energy, hi-tech, healthcare, medical devices, rail and semiconductor industries.

Job Requirements

Who We Are

Quest Global delivers world-class end-to-end engineering solutions by leveraging our deep industry knowledge and digital expertise. By bringing together technologies and industries, alongside the contributions of diverse individuals and their areas of expertise, we are able to solve problems better, faster. This multi-dimensional approach enables us to solve the most critical and large-scale challenges across the aerospace & defense, automotive, energy, hi-tech, healthcare, medical devices, rail and semiconductor industries.

We are looking for humble geniuses, who believe that engineering has the potential to make the impossible possible; innovators, who are not only inspired by technology and innovation, but also perpetually driven to design, develop, and test as a trusted partner for Fortune 500 customers. As a team of remarkably diverse engineers, we recognize that what we are really engineering is a brighter future for us all. If you want to contribute to meaningful work and be part of an organization that truly believes when you win, we all win, and when you fail, we all learn, then we’re eager to hear from you.

The achievers and courageous challenge-crushers we seek have the following characteristics and skills:

Summary

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 HW image quality that feeds on-device AI features. A significant part of the job is characterizing camera hardware performance in ways that predict whether those AI features will work, then building the setups, methods and automation to measure it. Established image-quality expertise is the foundation you bring — applied through targeted studies and cross-functional optimization rather than routine metric-by-metric validation.

What You Will Do

• Design and build validation methods for performance across vision and other sensing AI use cases — establishing the distances, environmental 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 gesture, audio, 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 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 multii-camera combined performance and interactions/coexistence under environmental and system stress, including temperature, ambient brightness extremes and thermally or power-constrained operation.
• Plan and execute system-level camera validation across photo, video and streaming capture in service of the AI use cases above; apply classic objective image-quality metrics (e.g. MTF) through targeted DOEs and cross-functional optimization support, rather than routine full-coverage validation runs.
• Document methods and results so that tests can be repeated and results defended by others.

Work Experience

What You Will Bring

• Masters Degree with 6-10 years of experience and background in Imaging Science,Computer Science, Image Processing, Computer vision, Optics, Electrical Engineering, or a related field, with substantial relevant industry experience in ISP, computer vision or Image Quality Testing.
• Demonstrated hands-on experience validating consumer imaging systems against objective image quality metrics, with working knowledge of industry image quality test protocols, charts and evaluation tools.
• Practical under
• standing 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.
• Working knowledge of camera geometric calibration — interpreting and applying an intrinsic/distortion calibration file to dewarp imagery (e.g. with OpenCV), and familiarity with camera–IMU and cross‑sensor temporal synchronization

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 SLAM / visual‑inertial (6DoF) localization, gaze/eye‑tracking or hand‑tracking — including the geometric‑accuracy and calibration considerations these systems depend on, and test design involving human subjects and inter‑subject variability.
• Experience with subjective and perceptual image quality evaluation alongside objective metrics.