Embedded CV ML Engineer — Edge AI for Care Tech

Sensio; Oslo; Sur place; NOK 1 000 000 - 1 400 000; Plein temps

Avantages offerts par ce poste

Cross-functional team

Ownership and growth opportunities

Norwegian product environment

International ambitions

Résumé du poste

Sensio is a leading European care technology company based in Norway. As a Machine Learning Engineer, you will work on training and evaluating computer vision models that run on embedded devices, balancing performance, memory and power in real care environments.

You will collaborate with hardware, software, product and data science teams to ensure reliable models, contributing to safer, more personalized care and impactful technology across international markets.

Qualifications

• Master's degree or PhD in machine learning, computer science, robotics, signal processing or related field.
• Strong experience with computer vision.
• Experience developing, training, validating and optimizing ML models for embedded devices or resource-constrained hardware.

Responsabilités

• Training, validating and improving computer vision models.
• Optimizing models for embedded devices and resource-constrained hardware, including performance, memory use and power consumption.
• Working with sensor data to improve model precision and robustness.
• Exporting, testing and preparing models for deployment.
• Collaborating with embedded, software, product and data science colleagues to ensure models work reliably in real-world care environments.

Connaissances

Computer vision

Embedded ML

Python

Edge AI

Formation

Master's or PhD in ML/CS/ robotics

Outils

PyTorch

C++

Embedded Linux

OpenCV

Description du poste

Sensio is a leading European care technology company based in Norway. As a Machine Learning Engineer, you will work on training and evaluating computer vision models that run on embedded devices, balancing performance, memory and power in real care environments.

You will collaborate with hardware, software, product and data science teams to ensure reliable models, contributing to safer, more personalized care and impactful technology across international markets.