Job Description & Details
This is a heavy-duty validation engineering role focused on next-generation consumer wearable hardware, where you'll be building testing frameworks and methodologies that don't exist yet. If you enjoy bridging the gap between raw hardware performance, optical lab setups, and on-device multimodal AI features, this position offers a massive technical playground.
What You'll Actually Be Doing
You will spend your days designing and constructing custom test capabilities from the ground up, including opto-mechanical fixtures, controlled lighting scenarios, and motion rigs for pre-production hardware. A large part of the work involves bringing up devices, flashing firmware, and writing robust Python scripts to automate data capture and analyze image, video, and sensor metrics at scale. You'll constantly investigate root-cause capture failures on early hardware and collaborate directly with software and hardware teams to figure out why an AI feature is degrading under thermal or power constraints.
The Core Tech Stack
You need deep, hands-on expertise in camera characterization and objective Image Quality (IQ) metrics like MTF, combined with strong production-level Python (specifically using OpenCV and NumPy for image/video analysis). Familiarity with ADB, device bring-up, flashing, and shell scripting is non-negotiable since you'll be wrangling pre-production wearable prototypes. Experience coming straight out of companies building consumer electronics, hearables, or wearables is heavily favored here.
Interview Expectations
Expect the hiring team to hand you an ambiguous scenario where an on-device vision AI feature is failing under low-light or high-motion conditions, and they will want you to whiteboard a complete test methodology from scratch including the lab setup, target selection, and data volume required to prove your hypothesis. They are also likely to quiz you on camera geometric calibration and temporal synchronization between the camera and IMU, listening closely to see if you understand how lens distortion and sensor latency directly break downstream perception algorithms.
Application Advice
Your resume needs to heavily emphasize your optical lab background and custom automation work rather than just running pre-existing test scripts. Make sure to explicitly include keywords like camera validation, image quality (IQ), camera characterization, OpenCV, NumPy, and device bring-up so you easily clear the ATS, and frame your past achievements around building validation infrastructure from scratch for consumer hardware.