You will join a hands-on development team that fosters engineering excellence, creativity, and innovation. Put your creativity, hardware background, programming, and problem-solving skills to the test. Adapt quickly to new technical areas, and deeply engage cross-functional teams to address problems. In this role, you will be responsible for all aspects of a large-scale lab crafted for testing new Hardware and Firmware.
As a Validation Engineer, you will play a central role in ensuring the quality and readiness of our next-generation hardware and firmware.
Your responsibilities will include:
Lab Development & Operations – Design, build, and operate a large-scale automation lab capable of testing multiple products simultaneously.
Test Execution & Debug – Develop and manage automated test suites, triage lab failures, and drive root-cause analysis to closure.
Cross-Functional Integration – Integrate deliverables from multiple R&D teams across us, ensuring seamless end-to-end validation and on-time product delivery.
Automation & Tooling – Create and maintain frameworks, scripts, and infrastructure that improve test coverage, efficiency, and reliability.
AI-Assisted Development – Leverage Generative AI tools and techniques to accelerate code development, automate test generation, and enhance engineering productivity.
Continuous Improvement – Identify gaps in existing validation processes and propose innovative solutions that raise the quality bar for future programs.
Minimum Qualifications
BS in Computer Science, Electrical Engineering, or a related field (or equivalent experience).
Proficiency in Python, C++, or other programming languages.
A hands-on problem-solver with a genuine passion for validation – finding issues, understanding them, and driving them to resolution.
Self-motivated with the ability to work independently and thrive in a collaborative team environment.
Preferred Qualifications
Experience in SoC, system-level, or hardware integration testing.
Familiarity with lab automation frameworks, test infrastructure, or CI/CD pipelines.
Exposure to firmware validation, hardware bring-up, or failure analysis workflows.
Experience or interest in using Generative AI tools (e.g., LLM-based coding assistants) to write, review, or optimize engineering code.
Strong communication skills and comfort working across multiple engineering disciplines.
