Software Quality Engineer - AI Inference

About the role

d-Matrix builds AI inference hardware and software, and is hiring a Software Quality Engineer in Belgrade to join its Quality Engineering team. The role combines software development skills with testing experience to assess functional behavior, numerical accuracy, performance and stability across the software stack and supported hardware. Automation and practical AI use are central: you will use AI to draft test plans, write test code and analyze logs, and verify its output against requirements and observed behavior.

Key responsibilities

• Translate requirements, changelogs and engineering handoffs into test plans with scope, configurations, expected results and evidence.
• Build and maintain automated functional, integration and end-to-end tests, integrated into CI, nightly and release workflows.
• Run qualification against the exact candidate build and configuration, recording hardware, software versions, commands, inputs and results.
• Investigate failures using code, logs and experiments, distinguishing product defects from environment problems and unreliable tests.
• Report defects with reproducible steps and evidence, verify fixes and document unresolved results and coverage gaps.
• Assess numerical accuracy, performance and stability against agreed tolerances and baselines.
• Prioritize coverage against product risk and available hardware, and document workflows so another engineer can execute them.

Required profile

• Strong software development ability and practical software quality or test engineering experience, including reading application or systems code and debugging beyond surface test failures.
• Experience designing tests from requirements, including negative cases, boundary conditions and integration behavior.
• Experience investigating failures with logs and reproducible experiments, and working with developers to verify fixes.
• Evidence of improving a workflow through automation and reusable tooling, and of using AI-assisted engineering for test planning, coding or failure analysis.
• Ability to work in Linux-based environments, with version control, code review and automated test workflows.
• Clear written communication, sound judgment about risk and uncertainty, and ability to collaborate with distributed teams.

Required skills

• Programming suitable for test automation; Python is used in the current workflow.
• Preferred: 2+ years of systems software testing (firmware, drivers, compilers, runtimes, distributed systems, real devices).
• Preferred: ML inference experience (model execution, numerical comparisons, quantization, performance benchmarks).
• Preferred: Python test frameworks, CI pipelines, containers, test-result reporting, lab automation, hardware-in-the-loop testing, C++.