Do you get excited when your ML models interact with the physical world?
Are you ready to learn the new exciting world of smart robots?
Do you strive in a fast paced and dynamic (startup) environment?
Would you like to cooperate with top professionals in our industry?
If your answers are mostly yes, then keep on reading.
At Nomagic, we’re on a mission to automate human repetitive manual tasks with intelligent robotics.
We’re now looking for a Machine Learning Applied Researcher, who’s ready to deep dive into the hard problems of understanding the real world (trying to match with software the millions of years of development leading to the human hand + eye) and share ML engineering experience and ideas with our amazing team.
See a short sneak peak of our product here: https://youtu.be/RQv_rbU8ffw
responsibilities :
Research cutting edge deep learning approaches and apply it to robotic handling of a vast variety of objects
Increase our robots dexterity by collaborating with the hardware team on real-world, physical innovations
Productionize novel approaches to anomaly detection (e.g. product disassembling in motion)
Automate data and model retraining pipelines
Use data to influence company-level strategic decisions
Evaluate and monitor ML models in production, detect data drifts and other reasons for degraded performance
requirements-expected :
Masters degree in Computer Science, related field or equivalent industry experience
Very good knowledge in deep learning and computer vision
Experience working in ML projects from inception to real-world deployment or research publication
Technical capabilities to understand, expand and debug deep learning models for computer vision
Drive to see final outcomes: from proof of concept to productionization
Great problem solving skills and advanced knowledge of Python
Excellent data analysis and communication skills
Fluent communication in English
offered :
Play with robots every day
Salary: 18-22k gross UoP per month + significant equity
Hybrid mode of work: 2 office days/week
Relocation package
Truly flexible working hours
No late evening calls - the entire team is based in Europe :)
English-speaking environment
benefits :
sharing the costs of sports activities
private medical care
sharing the costs of professional training & courses
