About Navflex
At Navflex, we're pioneering the future of logistics automation through cutting-edge AI and
robotics. Our autonomous mobile robots (AMRs) are transforming the way goods are loaded
and unloaded, enabling plug-and-play solutions that streamline operations and enhance
efficiency across the global supply chain for some of the world’s most demanding warehouse
Environments. Our international, cross‑disciplinary team in the EU and USA pairs robust mechatronics with cutting‑edge navigation and perception to deliver safe, reliable autonomy in real‑world warehouses and yards. Join us in shaping the future of intelligent logistics.
What makes us different
We bring hardware and AI into production, not just prototypes
We work directly with real warehouse operations and customer environments
We build systems that must be safe, reliable, and economically viable
What you can expect at the Munich Team
You will join a highly skilled, hands-on engineering team working at the intersection of robotics, product development, and real-world deployment, with direct impact on systems used by global customers.
What We Offer
The opportunity to work on robotics systems that are already used in real-world environments
A role where you can actively shape systems and see the impact of your work
A collaborative, international team with diverse backgrounds and perspectives
Plenty of room for personal and professional growth as we continue to scale
Challenging work alongside experienced engineers who are passionate about what they do
A culture that values ownership, learning, and continuous improvement
Competitive compensation
The Role
You will own system-level validation of Navflex’s autonomous forklift AMR—by continuously testing new software on real vehicles, stress-testing the system against the operational domain, and building automated test infrastructure that closes the gap between lab results and field performance.
This is not a “ticket-only QA” role. You will reproduce issues, analyze logs and data, and drive investigations far enough to pinpoint the most likely subsystem (perception, localization, planning, controls, HW interface, fleet services) and the fastest path to root cause and fix.
Success Measures - Success in this role will be measured by:
Regressions are caught early and software is released with evidence-based readiness.
Test coverage expands across the operational design domain (ODD), including edge cases and failure modes.
Field issues become reproducible in lab/replay/HIL with clear fault isolation and actionable engineering feedback.
A scalable automation framework exists (SIL/HIL + log replay + on-robot tests) with dashboards and automated reporting.
What You’ll Do
Own scenario-based validation across the operational domain
Define and maintain an Operational Design Domain (ODD) and scenario library that reflects real warehouse and trailer-loading workflows (normal operation, edge cases, abuse cases).
Translate requirements and known risks into testable acceptance criteria, pass/fail metrics, and release gates.
Design and execute functional, regression, performance, reliability, and safety validation plans at the system level.
Plan long-duration stability/endurance campaigns and track reliability trends over time.
Continuously test software on real vehicles (lab + field)
Own day-to-day test execution on a vehicle fleet: smoke tests, nightly/weekly regressions, and targeted experiments for new features and bug fixes.
Run structured test sessions that intentionally challenge autonomy behavior in a safe, controlled way (tight spaces, occlusions, pallet variability, trailer geometry, degraded sensors, etc.).
Support pilots and customer transitions; ensure evidence-based sign-off for rollout and ramp.
Debug, reproduce, and isolate issues using logs and data
Reproduce failures using on-robot tests, log replay, simulation, and HIL as appropriate.
Analyze logs/traces and recorded datasets (e.g., ROS bag files, telemetry, event logs) to identify failure signatures and likely root causes.
Create high-signal bug reports with minimal repro steps, expected vs. actual behavior, and supporting evidence (plots, log snippets, metrics).
Partner with engineers to drive issues to closure and prevent regressions.
Build automated test infrastructure (SIL/HIL + reporting)
Develop automated test scripts that run against simulation and log replay, and extend them to execute on physical robots where feasible.
Design and implement Hardware-in-the-Loop (HIL) capabilities to validate critical interfaces and autonomy behavior without always needing a full vehicle-in-the-loop setup.
Integrate automated tests into CI/CD (per-PR, nightly, and release-candidate runs).
Build tooling to compare expected vs. actual vehicle behavior from logged data; establish dashboards for coverage, pass rates, and reliability trends.
Automate test reporting and release readiness summaries for engineering, product, and operations stakeholders.
Improve test process and raise the quality bar
Own test request intake: guide developers to the right validation method (unit/integration/system/HIL/field) and prioritize by risk and impact.
Continuously refine workflows to improve coverage, safety, and confidence in every release.
Mentor junior engineers and contribute to best practices in testing, documentation, and safe operations around robotic hardware.
What You’ll Bring
Systems-level mindset and comfort reasoning about a complex robotics stack and failure modes.
Strong debugging discipline and hands-on comfort with physical robots in lab and field environments.
Clear communication and an evidence-based approach to feedback and decision-making.
Ownership mentality: you take responsibility for quality outcomes, not just test execution.
Qualifications
Bachelor’s degree or higher in Robotics, Computer Science, Electrical Engineering, Mechanical Engineering, Mechatronics, or related field (or equivalent practical experience).
5+ years in system testing, validation, integration testing, or quality engineering for complex electromechanical products (robotics, autonomous systems, vehicles, industrial automation, or similar).
Python proficiency for test automation and data analysis; ability to read and navigate C++ codebases strongly preferred.
Strong Linux proficiency and experience with Git-based workflows.
Experience designing structured test plans and executing them with clear pass/fail criteria and documentation.
Professional fluency in English.
Willingness to travel up to 20% of the time.
Preferred, But Not Required
Experience testing AMRs/AGVs, autonomous forklifts, or other mobile robots in production environments.
Experience with ROS or ROS 2 (introspection tooling, bagging/replay, launch/test utilities).
Experience with simulation or digital twin environments (e.g., Gazebo, Isaac Sim, Webots, Unity) and sim-to-real validation practices.
Experience with HIL/SIL test setups, fault injection, and long-duration stability testing.
Experience validating API contracts and distributed systems that interface with robot fleets (fleet manager, telemetry pipeline, integrations).
Familiarity with safety standards relevant to driverless industrial trucks (e.g., ISO 3691-4) and safe testing practices around heavy equipment.
Experience with test management/bug tracking tools (e.g., ClickUp, TestRail) and building metrics dashboards.
German language proficiency.
Work Environment & Safety
This role involves hands-on work around industrial robotic equipment. You must be able to follow safe operating procedures, work in warehouse environments (noise, dust, temperature variation), and support occasional after-hours or weekend test windows when needed for deployments. Navflex is an equal opportunity employer.
