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Xirgo • Enschede, Overijssel, Netherlands
Role & seniority: Senior QA Engineer (AI) focused on AI/ML validation for embedded/edge and cloud systems.
Stack/tools: Embedded/edge AI test automation (Python), HIL, simulation, in-vehicle testing; telemetry/log analysis; Wireshark, Drewlinq, serial loggers, oscilloscopes, power analyzers; JIRA; TestRail, Postman.
AI Quality & Integration: validate end-to-end AI features (computer vision, ADAS, DMS) across device, edge, and cloud; build data-driven feedback to diagnose performance and improve real-world outcomes.
AI Models Test Planning & Automation: design/maintain test plans, suites, reusable automation for embedded/edge AI and video analytics; own QA artifacts and test coverage across devices and platforms; develop/extend Python-based test frameworks for HIL, simulation, and in-vehicle testing.
Execution & Systems Validation: run functional, regression, stress, and performance tests on firmware features (ADAS, DMS, A/V, OTA, GNSS/Wi‑Fi); instrument systems and analyze defects across firmware and cloud layers.
Bachelor's or Master’s in CS, E/E or related field; or equivalent experience.
5+ years in QA/systems engineering with embedded/IoT; 3+ years in AI/ML/computer vision.
Strong QA methodologies, testing types, and best practices; test automation experience (Python) for embedded/edge.
Ability to interpret hardware/software interactions; strong debugging, analytical, communication, and or
QA (AI) Engineer
Driving The Future of Smart Fleet Logistics
At Xirgo, we’re not just transforming logistics — we’re redefining what’s possible. Let’s move forward together.
Our Purpose
We believe smarter tools create smarter operations. As the switched-on experts in IoT fleet solutions, we transform uncertainty into confidence, complexity into clarity, and data into decisions.
Our Vision
We empower partners with intelligent fleet logistics to create a more connected future. From bustling cities to open highways, from railroads to runways, our innovative technologies make peace of mind the new normal.
Our Mission
To be the world’s most trusted partner in smart fleet logistics, delivering comprehensive IoT solutions that transform data into useful information. We enhance fleet safety, efficiency, and performance—ensuring confidence at every step.
About The Role
We’re hiring a QA Engineer (AI) to ensure our next‑generation video dashcam platform delivers reliable, high‑performance AI features that bring real‑world value to fleet operators and drivers. You’ll sit at the intersection of product, engineering, and customer success—validating AI/ML capabilities end‑to‑end and building automation that scales quality across embedded systems and cloud services.
What You'll Do
AI Quality & Integration
Validate end‑to‑end behavior of AI features (e.g., computer vision, ADAS, DMS) across device, edge and cloud. Build data‑driven feedback loops to diagnose performance issues, tune models, and improve real‑world outcomes.
AI Models Test Planning & Automation
Think automation first: design and implement test plans, suites, and reusable automation for embedded/edge AI and video analytics. Create and maintain test documentation; own QA artifacts (plans, cases, reports) and ensure coverage across devices, platforms, and browsers. Develop and extend Python‑based test frameworks (or equivalent) for HIL (hardware‑in‑the‑loop), simulation, and in‑vehicle testing
Execution & Systems Validation
Run functional, regression, stress, and performance tests on firmware features: ADAS, DMS, A/V recording, live streaming, OTA updates, GNSS/Wi‑Fi location, power management, and protocol stacks. Instrument systems to capture telemetry, logs, and metrics; analyze defects across firmware and cloud layers.
Tooling, Debugging & Issue Management
Use tools such as Wireshark, Drewlinq, serial loggers, oscilloscopes, and power analyzers to verify data flow and system stability. Document issues clearly in JIRA (or similar), with reproducible steps and evidence; collaborate with developers to resolve root causes.
Collaboration & Customer Enablement
Work cross‑functionally with product managers, software/firmware, and hardware teams to translate requirements into actionable testable deliverables. Proactively identify process gaps and drive continuous improvement in our verification and release practices.
Required
Qualifications / Experience
Bachelor's or Master’s in Computer Science, Electrical/Electronic & Systems Engineering, or related field (or equivalent experience). 5 years in QA or systems engineering with embedded/IoT devices and/or 3+ years in AI/ML applications/computer vision. Strong grasp of QA methodologies, testing types (functional, performance, stress, regression), and best practices. Experience with test automation (preferably Python) and frameworks for embedded/edge systems. Ability to interpret hardware/software interactions; excellent debugging, analytical, communication, and organization skills. Comfortable operating independently in a fast‑paced, collaborative environment.
Preferred
Exposure to real‑time video processing, edge AI, or dashcam technologies. Experience with vehicle/video telematics, power optimization, or environmental robustness.
Tools proficiency: TestRail, Postman, Wireshark, log/telemetry analysis. Understanding of fleet safety, telematics, or automotive camera systems.
Why Xirgo
Build safety‑critical AI features that matter to drivers and fleets. Work across device, edge, and cloud, with real customers and real data. Competitive salary and benefits, plus training, development, and growth opportunities.
Research & Development
Enschede, Netherlands
Mallusk Newtownabbey, United Kingdom