Embedded ML Engineer for Edge AI in Care Tech

forsker innen datavitenskap; Oslo; Sur place; NOK 900 000 - 1 200 000; Plein temps

Résumé du poste

Sensio, a leading European care technology company, is seeking a Machine Learning Engineer to work on training and evaluating computer vision models for embedded devices. You will balance performance, precision, robustness, memory, and power constraints in real care environments.

You will join a strong product and engineering team where hardware, software, data and ML collaborate closely to improve safety and efficiency in care settings.

Qualifications

• A master’s degree or PhD in machine learning, computer science, robotics, signal processing or a related field
• Solid experience with computer vision
• Experience developing, training, validating and optimizing ML models for embedded devices or resource-constrained hardware
• Strong Python skills and experience with ML frameworks such as PyTorch
• Experience working close to hardware, preferrably with sensors, depth cameras, time-of-flight data, robotics, drones, automotive systems or similar
• Understanding of inference on edge 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, including depth, time-of-flight or similar data sources, to improve model precision and robustness
• Exporting, testing and preparing models for deployment
• Building systems for continuous improvement, experiment tracking, model evaluation and feedback loops
• Collaborating closely with embedded, software, product and data science colleagues to ensure that models work reliably in real-world care environments

Connaissances

Computer vision

Python

Edge ML

Embedded hardware

Model deployment

ML frameworks

Formation

Master’s or PhD in ML/CS/Robotics

Outils

PyTorch

C++

Description du poste

Sensio, a leading European care technology company, is seeking a Machine Learning Engineer to work on training and evaluating computer vision models for embedded devices. You will balance performance, precision, robustness, memory, and power constraints in real care environments.

You will join a strong product and engineering team where hardware, software, data and ML collaborate closely to improve safety and efficiency in care settings.