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!
Teltonika’s Telematics business unit develops and produces easy-to-use GPS tracking devices for effective fleet management across logistics, agriculture, car sharing, construction, and more. We use the latest technologies to set new standards for the telematics industry.
If you want to shape how AI models run at the edge on real embedded hardware, not just in a notebook, this is the team for you!
In this role, you will:
- 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.
What we expect of you:
- 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.
Ideally, you’ll also have:
- 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!
What we offer:
- 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
Skills Required
- 2+ years of experience in AI/ML model development, evaluation, or deployment
- Solid Python skills
- Practical experience with machine learning frameworks such as PyTorch or TensorFlow
- Experience testing and benchmarking models for accuracy, latency, and resource usage
- Understanding of inference constraints on embedded or edge hardware, including CPU, GPU, NPU, memory, and power limitations
- Comfort working across Linux and Windows environments
- Strong analytical skills and ability to independently investigate and solve technical problems
- Professional working proficiency in English
- Experience with edge inference runtimes or toolchains such as TensorFlow Lite, ONNX Runtime, TensorRT, or vendor NPU SDKs
- Experience with computer vision models for ADAS/DMS, including object detection, driver monitoring, or event classification
- Experience with C or C++ for embedded model integration
- Familiarity with embedded Linux and camera/video pipelines such as V4L2 or GStreamer
- Experience with cloud ML infrastructure, model serving, MLOps pipelines, or containerized inference
- Bachelor's degree in Computer Science, Data Science, Electronics Engineering, or a related field
Teltonika IoT Group Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Teltonika IoT Group and has not been reviewed or approved by Teltonika IoT Group.
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Healthcare Strength — Core medical coverage is commonly included, with private/additional health insurance in many regions and options like psychological counseling and dental in some locations. In certain roles, coverage can extend to family members.
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Leave & Time Off Breadth — Paid vacation, sick leave, and extra personal days such as a birthday day off are noted across multiple locations. Some regions also highlight summer-hour schedules and robust annual leave frameworks.
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Strong & Reliable Incentives — Sales compensation includes uncapped commissions and sizable bonuses for top performers. High achievers are positioned to see significant earnings upside.
Teltonika IoT Group Insights
What We Do
Teltonika IoT Group is a Lithuanian high-tech company group that designs, develops, and manufactures Internet of Things (IoT) devices and solutions for businesses, operating in niches such as telematics, networking, telemedicine, and EV charging.
