Embedded CV ML Engineer — Edge AI for Care Tech

Sensio

Oslo

On-site

NOK 1,000,000 - 1,400,000

Full time

5 days ago
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Benefits offered by this job

Cross-functional team
Ownership and growth opportunities
Norwegian product environment
International ambitions

Job summary

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.

Responsibilities

  • 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.

Skills

Computer vision
Embedded ML
Python
Edge AI

Education

Master's or PhD in ML/CS/ robotics

Tools

PyTorch
C++
Embedded Linux
OpenCV

Job description

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.

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