AI engineer for edge devices

We are looking for AI Engineer to join our R&D team in Warsaw, Poland. You will join one of the teams developing our next-generation video telematics devices and be responsible for analyzing, selecting, testing, and deploying machine learning models used for on-device (edge) inference, PC-based validation, and — going forward — cloud-based processing of data collected from our devices. We'd love to walk you through all the details during the recruitment process!

• Analyze, select, and evaluate machine learning models for specific use cases and problem-solving needs (e.g. ADAS/DMS, video/image analysis, sensor and CAN data processing).
• Test, benchmark, and configure AI models for deployment on embedded edge devices, as well as on PC (Windows, Linux) platforms.
• Analyze system capabilities (CPU, GPU, NPU, memory, power budget) and contribute to selecting hardware of appropriate specification for AI workloads.
• Optimize models for resource-constrained edge hardware (quantization, pruning, conversion to inference runtimes such as TensorFlow Lite, ONNX Runtime, or vendor-specific SDKs).
• Design the data flow between edge-level pre-processing and any future cloud-based models that further process data collected from edge AI devices.
• Collaborate with embedded software and hardware teams to integrate models into the media/data pipeline of our video telematics devices.
• Track current and emerging AI/ML trends and evaluate their applicability to company products.
• Document model performance, testing methodology, and deployment decisions.
• Participate in Agile/Scrum team processes and decision making.

• 2+ years of experience in AI/ML model development, evaluation, or deployment.
• Solid Python skills and practical experience with ML frameworks (PyTorch, TensorFlow, or similar).
• Experience in testing and benchmarking models for accuracy, latency, and resource usage.
• Understanding of the constraints of running inference on embedded/edge hardware (CPU/GPU/NPU limitations, memory, power).
• Comfortable working across both Linux and Windows environments.
• Strong analytical skills and the ability to independently investigate and solve technical problems.
• Professional working proficiency in English.
• Будет плюсом: Experience with edge inference runtimes and toolchains (TensorFlow Lite, ONNX Runtime, TensorRT, or vendor NPU SDKs such as NXP, Qualcomm, Mediatek, Rockchip RKNN, or similar); Experience with computer vision models relevant to ADAS/DMS (object detection, driver monitoring, event classification); Experience with C/C++ for integrating models into embedded applications; Familiarity with embedded Linux and camera/video pipelines (V4L2, GStreamer); Experience with cloud ML infrastructure (model serving, MLOps pipelines, containerized inference); Bachelor's degree in Computer Science, Data Science, Electronics Engineering, or a related field; Any other relevant experience that you think makes you a great fit!

• Private medical care (Medicover Premium) and a MultiBenefit cafeteria
• Unique opportunities to grow professionally being part of a challenging and high-growth environment
• Interesting and ambitious projects of industrial GPS tracking devices
• Additional day off for your birthday
• Team building activities