Machine Learning Engineer
Job in
Zürich, 8081, Zurich, Kanton Zürich, Switzerland
Listed on 2026-09-25
Listing for:
Kanadevia Inova AG
Full Time
position Listed on 2026-09-25
Job specializations:
-
Software Development
Machine Learning/ ML Engineer, AI Engineer (Applied/Software)
Job Description & How to Apply Below
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.
At Kanadevia Inova, we pride ourselves on being at the forefront of waste-to-X technology. We are not just waste managers; we are creators of value from what communities discard. Your role at Kanadevia Inova directly contributes to turning something once considered useless - waste - into something invaluable: energy, heat, hydrogen, fertilizer, and beyond.
Job Description- 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.
- 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, Tensor Flow, 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.
For HR agencies:
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