Edge AI Software Engineer

XpertDirect; Helsinki; On-site; EUR 90,000 - 130,000; Full time

Job summary

XpertDirect in Helsinki is seeking an experienced Edge AI Software Engineer to build software that runs ML models directly on embedded hardware. You will develop high-performance C++ software for real-time edge applications and optimise models for constrained devices.

Collaborating with ML, Embedded, and Systems teams, you will deploy TensorFlow Lite/ONNX workflows on ARM-based platforms, ensure efficient memory and power usage, and improve reliability of edge AI systems in real-world tests.

Qualifications

• 4+ years in Embedded Software, Edge AI, Embedded Linux or related roles.
• Commercial Embedded Linux software development experience.
• Experience with ARM-based hardware.
• Hands-on deployment/optimisation of ML models for edge devices.
• Python development for automation, testing or ML workflows.
• Understanding of memory, CPU latency and power constraints.
• Strong Linux debugging and performance-analysis skills.

Responsibilities

• Deploy ML models onto ARM-based embedded platforms.
• Develop high-performance C++ software for real-time edge apps.
• Optimise TensorFlow Lite models for latency and memory usage.
• Integrate AI inference into Embedded Linux applications.
• Build software that processes sensor/vehicle data at the edge.
• Profile and optimise model performance on constrained hardware.
• Develop Python tooling for model conversion, testing and deployment.
• Collaborate with ML engineers to move models from experiments to production.

Skills

Embedded Software

Edge AI

C++

Python

Linux

Machine Learning

Tools

ARM-based hardware

TensorFlow Lite

ONNX Runtime

NVIDIA Jetson

Buildroot/Yocto

CAN / Automotive Ethernet

Job description

Smart Mobility | Edge AI | Connected Vehicles | Embedded Systems

Our client, an innovative Smart Mobility technology company based in Helsinki, is developing intelligent systems for connected vehicles and next-generation transport infrastructure.

They're looking for an Edge AI Software Engineer to bring machine learning directly onto embedded hardware—building software that can process sensor data and run AI models locally, efficiently, and in real time.

This role sits at the intersection of Embedded Software, Machine Learning, and Intelligent Mobility.

What You'll Be Working On

• Deploying machine learning models onto ARM-based embedded platforms
• Developing high-performance C++ software for real-time edge applications
• Optimising TensorFlow Lite models for latency, memory consumption, and computational efficiency
• Integrating AI inference into Embedded Linux applications
• Building software that processes sensor and vehicle data directly at the edge
• Profiling and optimising model performance on resource-constrained hardware
• Developing Python tooling for model conversion, testing, benchmarking, and deployment
• Working with Machine Learning Engineers to move models from experimentation into production hardware
• Collaborating with Embedded and Systems Engineers on hardware/software integration
• Testing and validating edge AI systems under real-world operating conditions
• Improving reliability, observability, and update mechanisms for deployed edge software

Experience Required

• 4+ years of experience in Embedded Software, Edge AI, Embedded Linux, or related engineering roles
• Commercial experience developing software for Embedded Linux environments
• Experience working with ARM-based hardware
• Hands‑on experience deploying or optimising machine learning models for edge devices
• Python development experience for automation, testing, or ML workflows
• Good understanding of memory, CPU, latency, and power constraints in embedded systems
• Strong Linux debugging and performance-analysis skills

Nice to Have

• TensorFlow Lite, ONNX Runtime, or comparable edge inference frameworks
• NVIDIA Jetson or Qualcomm platforms
• Computer vision or sensor‑fusion experience
• CAN, automotive Ethernet, or vehicle communication protocols
• Yocto or Buildroot
• Model quantisation, pruning, or hardware acceleration
• Previous experience in Smart Mobility, Automotive Technology, Connected Vehicles, Robotics, or Intelligent Transport Systems