Machine Learning Engineer
Job Location:
Job Location:
Zürich - Switzerland
Monthly Salary:
Not Disclosed
Monthly Salary:
Posted on:
Yesterday
Posted on:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
- Industrialise and operate AI/ML solutions by transforming prototypes into scalable production-ready applications.
- Design implement and maintain end-to-end MLOps pipelines covering training validation deployment monitoring and retraining.
- Collaborate closely with Data Scientists Data Engineers Software Engineers Product Managers and business stakeholders to deliver AI solutions.
- Ensure reliability security compliance data integrity performance and governance throughout the machine learning lifecycle.
- Monitor and optimise model performance troubleshoot production issues and support continuous improvement while mentoring less experienced colleagues.
Qualifications :
- MSc in Computer Science or a STEM field with a strong computer science focus plus experience working in agile software development environments.
- Strong Python programming skills and hands-on experience with machine learning frameworks such as PyTorch TensorFlow or Scikit-learn.
- Solid understanding of MLOps practices including model deployment versioning monitoring and lifecycle management in production environments.
- Experience with cloud platforms (preferably Azure) containerisation technologies (Docker) APIs databases and distributed systems.
- Knowledge of data engineering and data processing frameworks; experience with industrial IoT time-series data computer vision or Physics-AI solutions is advantageous.
Additional Information :
For HR agencies: Please note that we do not accept applications coming from agencies. Thank you.
Remote Work :
No
Employment Type :
Full-time
About Company
Welcome to Kanadevia Inova, a global innovation leader in the waste infrastructure space, where we believe in creating a sustainable future through technology and innovation. Transforming Waste into Value At Kanadevia Inova, we pride ourselves on being at the forefront of waste-to-X ... View more
