Embedded Quality Engineer - Camera
Summary
We are looking for an experienced and outcome-driven Embedded Quality Engineer - Camera to ensure that we deliver the best-in-class camera/ISP solution for Apple products! In this role, you will play a critical part in qualifying camera firmware and drivers, ensuring we ship a high-quality product that delights and inspires millions of Apple customers every day. As a member of our fast-paced group, you will have the outstanding and exciting opportunity to contribute to the development of upcoming products. This is a chance to make a significant impact on the camera experience for a global audience.
Description
In this role, you will:
Own end-to-end testing for assigned camera features across multiple platforms
Design and execute test plans covering functionality, performance, power, stability, and image quality
Build scalable automated tests and test tooling integrated with CI/CD pipelines
Perform exploratory manual testing to surface issues automation misses
Triage, reproduce, and root-cause defects in partnership with firmware and driver teams
Analyze results across builds to identify regressions, trends, and release risk
Minimum Qualifications
- BS and a minimum of 3 years relevant industry experience.
- 3+ years testing embedded systems, including authoring system and feature-level test plans
- Experience building test automation for embedded or firmware targets
- Proficiency in Python or a comparable scripting language
- Comfortable in macOS or Linux command-line environments
- Solid grounding in QA methodology and structured test process
Preferred Qualifications
- Experience shipping high-volume consumer hardware
- Hands-on image quality evaluation using charts, light boxes, or measurement equipment
- Experience with pre-silicon or early hardware bring-up validation
- Familiarity with debugging firmware via logs, traces, and instrumented builds
- Working knowledge of camera or imaging fundamentals: ISP pipeline, 3A, video formats, or color spaces
- Demonstrated use of with AI-assisted engineering tools and prompt construction to develop tools (e.g test authoring, log analysis, debugging ) to increase engineering throughput, plus a willingness to adopt new AI workflows into day-to-day test development