Software Quality Engineer, Serbia

Join d-Matrix and help build the future of AI inference. We’ve pioneered a memory-centric architecture that brings compute directly into memory, making AI faster, more energy efficient, and accessible on a global scale. From chips and software to rack-scale systems, our team is tackling some of AI infrastructure’s hardest challenges — and shipping breakthrough technology today. If you want to create what comes next and help make infinite inference possible, we’d love to hear from you.

Our culture is built on respect, collaboration, and direct communication. We value humility, we believe our different perspectives lead to better solutions, and we’re looking for people who are driven by execution and energized by hard problems.

Software Quality Engineer, Serbia

Location: Belgrade, Serbia

Role Overview

You will join d-Matrix’s Quality Engineering (QE) team as a hands-on software quality engineer, combining software development skills with testing experience to assess functional behavior, numerical accuracy, performance, and stability across our software stack and supported hardware configurations. You will translate requirements and engineering changes into clear test plans, build repeatable tests, investigate failures, and provide evidence that helps engineering and release owners make decisions. Automation and practical AI use are central to the role. You will use AI to draft test plans, write test code, and analyze logs, and you will verify its output against requirements and observed behavior. You will partner with QE, Product, and Engineering colleagues across locations. Your first priority is to learn an existing workflow, contribute to current qualification work, and improve it without disrupting delivery.

Responsibilities

Translate requirements, changelogs, and engineering handoffs into test plans with clear scope, configurations, expected results, and evidence.; Build and maintain automated functional, integration, and end-to-end tests, and integrate them into CI, nightly, and release workflows.; Run qualification against the exact candidate build and supported configuration, recording hardware, software versions, commands, inputs, and results so others can reproduce the run.; Investigate failures using code, logs, and focused experiments, distinguishing product defects from environment problems and unreliable tests.; Report defects with expected and actual behavior, reproducible steps, and evidence, then verify fixes and document unresolved results and coverage gaps.; Assess numerical accuracy, performance, and stability against agreed tolerances and reliable baselines, confirming expected behavior with engineering owners.; Use AI to assist test design, coding, and log analysis, reviewing outputs and verifying conclusions before relying on them, in line with approved data-handling rules.; Prioritize coverage against product risk and available hardware, and document workflows, results, and handoffs so another engineer can execute them.

Requirements

Strong software development ability and practical software quality or test engineering experience, including reading application or systems code and debugging beyond surface test failures.; Programming skills suitable for test automation and tooling, demonstrated by code you have built or maintained (Python is used in the current workflow).; Experience designing tests from requirements, including negative cases, boundary conditions, and integration behavior, and explaining what the tests do and do not establish.; Experience investigating failures with logs, configuration evidence, and reproducible experiments, and working with developers to verify fixes.; Evidence of improving a workflow through automation and reusable tooling, including how you verified correctness and managed maintenance.; Practical use of AI-assisted engineering for test planning, coding, or failure analysis, including how you review output and catch unsupported conclusions.; Ability to work in Linux-based development or test 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.

Nice to have

2+ years of experience; Systems software testing in firmware, drivers, compilers, runtimes, or distributed systems, including software running on real devices.; ML inference experience, including model execution, numerical comparisons, quantization, or performance benchmarks.; Experience with Python test frameworks, CI pipelines, containers, test-result reporting, or lab automation.; Hardware-in-the-loop testing, multi-card or multi-node configurations, and extended stability or soak testing.; Experience extending a test framework or introducing a human-reviewed AI workflow into repeated engineering use.; Experience with C++ or another systems language.