Edge AI Engineer – Mid/Senior

Teltonika

. Analyze, select, and evaluate machine learning models for use cases including ADAS/DMS, video/image analysis, and sensor and CAN data processing .

Posted 11/4/2026full-timeVilnius • LithuaniaSenior💰 €19 - €35 per hourWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI/ML model development and deployment, with strong proficiency in Python and experience with ML frameworks such as PyTorch and TensorFlow. Capable of optimizing models for embedded edge devices and collaborating effectively with cross-functional teams.

Highest-signal resume keywords

AI/ML Model DevelopmentPython ProgrammingEmbedded Edge Hardware OptimizationComputer Vision ModelsCloud ML Infrastructure

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning FrameworksModel Testing and BenchmarkingC/C++ ProgrammingQuantization and PruningData Flow DesignEdge Inference RuntimesAgile/Scrum MethodologiesTechnical Problem SolvingModel Performance DocumentationGPS Tracking Technologies

Soft Skills

Analytical SkillsIndependent Investigation

Tools & Technologies

TensorFlow LiteONNX RuntimeTensorRTNXP SDKQualcomm SDKMediatek SDKRockchip RKNNEmbedded LinuxV4L2GStreamer

Industry Keywords

ADASDMSVideo/Image AnalysisSensor Data ProcessingFleet ManagementLogisticsAgricultureCar SharingConstruction

Tech Stack

Tools & technologies

CloudLinuxPythonPyTorchTensorflowC++

About the role

Key responsibilities & impact

Analyze, select, and evaluate machine learning models for use cases including ADAS/DMS, video/image analysis, and sensor and CAN data processing
Test, benchmark, and configure AI models for embedded edge devices and PC platforms running Windows or Linux
Analyze CPU, GPU, NPU, memory, and power capabilities and contribute to AI hardware selection
Optimize models for resource-constrained edge hardware through quantization, pruning, and conversion to inference runtimes
Design data flow between edge preprocessing and future cloud-based models
Collaborate with embedded software and hardware teams to integrate models into video telematics device media/data pipelines
Track current and emerging AI/ML trends and evaluate applicability to company products
Document model performance, testing methodology, and deployment decisions
Participate in Agile/Scrum processes and decision making
Develop and produce technologies for GPS tracking and fleet management across logistics, agriculture, car sharing, construction, and other sectors

Requirements

What you’ll need

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 constraints of running inference on embedded/edge hardware, including CPU/GPU/NPU limitations, memory, and power
Comfortable 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 and toolchains such as TensorFlow Lite, ONNX Runtime, TensorRT, or vendor NPU SDKs such as NXP, Qualcomm, Mediatek, or Rockchip RKNN
Experience with computer vision models relevant to ADAS/DMS
Experience with C/C++ for integrating models into embedded applications
Familiarity with embedded Linux and camera/video pipelines such as V4L2 and 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 is ideally expected

Benefits

Comp & perks

Great opportunities to grow in a strong and rapidly expanding company
Interesting and ambitious projects of industrial GPS tracking devices
Hybrid work model in Vilnius and Kaunas, with the option to work fully remotely for candidates based elsewhere in Lithuania
Training courses, conferences or business trips
Dynamic, challenging work environment and cooperation-based internal culture
Flexible work schedules
Hybrid work opportunities
Health insurance
Company-paid sports activities (basketball, football, volleyball, yoga) and other sports events
Team building, summer festivals, and other important occasions
Opportunity for solid bonuses when participating in the recommendation program
Birthday and Christmas gifts
Rewards on work anniversaries
Office snacks
Bonuses may be available