Camera Validation Engineer

Meta Reality Labs is a world leader in the design of virtual and augmented reality systems.

Come work alongside technology visionaries and research scientists to create the technology that makes VR and AR pervasive and universal.

Join the adventure of a lifetime as we make science fiction real and change the world.As a Camera Validation Engineer on the Cameras & Depth team, you will support the development of next generation Computer Vision and RGB cameras.

You will work on innovating, developing and integrating hardware and algorithms for future generations of AR and VR devices.

Responsibilities:

Camera Validation Engineer Responsibilities:

Develop, validate, characterize, and perform objective and subjective IQ analysis for imaging systems

Work with internal teams for test readiness, troubleshoot and debug image, work with external vendors in bringing up testers, reviewing tester DFM, running GRRs

Design end-to-end validation solutions, including HW setup design, metric proposal, validation plan, implementation of test automation, draw valid conclusions

Manage image quality labs contributing to camera architecture, bring up, tuning, and qualification

Research, design, and develop tools for test creation and data analysis in JMP, Matlab, or Python

Triage and debug image quality related problems during development cycles

Manage and report image quality deliverables to cross-functional team to guide product development

Qualification and experience:

Minimum Qualifications:

Bachelor's Degree in Imaging Science, Mechanical, Electrical, Optical, Image Processing or related fields or equivalent relevant experience

3+ years of experience in image/video quality test, metrics, algorithms or evaluation methods for benchmarking or camera characterization (sensor, lens, module, device)

Experience evaluating camera optical/sensing, image processing techniques, ISP blocks or mainstream computational photography algorithms for mobile camera product

Experience implementing or creating and debugging image quality test infrastructure (hardware, charts, software, automation, opto-mechanical components, motion control stages and precision alignment components, optical filters, or lenses) and evaluation platforms (DXO, Imatest, IQ Analyzer, etc)

Experience with camera module fabrication, understanding how module component performance and assembly process impact the camera performance

Experience in Matlab or Python for operating lab systems, algorithm implementation, lab automation, data collection, or data analysis

Preferred:

Preferred Qualifications:

Masters Degree in Imaging Science, Color Science, Mechanical, Electrical, Optical, or related fields or equivalent relevant experience

5+ years of experience in image/video quality test, metrics, and evaluation methods for benchmarking or camera validation/characterization (sensor, lens, module, device)

Proven experience in Matlab or Python for operating lab systems, algorithm implementation, lab automation, image data collection, and JMP for analysis

Familiarity with ADB for data analysis

Contributions to ICPQ, IEEE or other IQ standards organizations, familiarity with industry image quality test protocols and standards in the market

Background in lab test and analysis for industry standard metrics

Familiarity with sensor and optics and their evaluation methodologies

Understanding of overall systems interactions in the image pipeline

Experience in one or more of the following areas: optical system design, sensor technology, imaging algorithms, camera ISP and computation photography features, imaging lab design and setup, software QA process

Hands-on experience working in an optical lab environment, creating, maintaining and operating sensitive measurement setups for quality data acquisition

Hands-on experience prototyping with macro-scale imaging test targets, interfacing fixtures for sensor devices, off-the-shelf optomechanical components (e.g. Thorlabs, Edmund, Newport)

Hands-on experience debugging image quality issues, finding root causes, and familiarity with image quality artifacts