Staff Quality Automation Engineer

The role

You will turn QE workflows, automation, and prototypes into reliable internal products. You will build reusable capabilities to improve how teams test and develop software and support engineers in delivering product releases.

What you will do

• Work with QE and Engineering to understand users' needs and agree priorities.
• Build and maintain shared automation, test frameworks and harnesses.
• Turn scripts and prototypes into tools others can use.
• Integrate tools with existing continuous integration, nightly and release workflows.
• Support adoption through documentation, examples and user feedback.
• Assess coverage, assertions, expected results and negative cases.
• Work with developers to verify fixes and provide testing cover.
• Keep up with advances in AI coding agents and workflow tools.

Required qualifications

• 5+ years of experience
• Strong software-development skills: write, debug and maintain code, explain design choices, review others' work and investigate failures
• Experience building shared test automation, frameworks or engineering tools that others use repeatedly
• Evidence of turning prototypes or manual workflows into reliable tools
• Practical test engineering: requirements, boundary and negative cases, coverage, and failure investigation using code, logs and reproducible experiments
• Experience with Linux, version control, code review, automated tests and CI workflows
• Regular use of AI coding agents or AI workflows

Nice to have

• Systems software testing in firmware, drivers, compilers, runtimes or distributed systems, including real devices
• ML inference, model execution, numerical comparisons, quantization or performance benchmarks
• Test frameworks, CI pipelines, containers, reporting or lab automation
• Hardware-in-the-loop, multi-card or multi-node configurations, and extended stability or soak testing
• Internal engineering products used across teams, or human-reviewed AI workflows used repeatedly

About the company

d-Matrix has pioneered a memory-centric architecture that brings compute directly into memory. The team works on chips, software, and rack-scale systems to tackle AI infrastructure challenges.