Machine Learning Engineer
CERN
CERN's healthcare AI team (CAFEIN) builds a federated AI platform that trains models on medical data across hospitals and research institutes without the data leaving those sites. The role is a hands-on ML engineering position working from experiments to production, focusing on model development, distributed deployment, privacy/security and data ingestion for medical data.
What you’ll do
- Designing and running ML experiments in Python (PyTorch, TensorFlow, JAX, scikit-learn)
- Deploying models on distributed infrastructure shared by several institutions
- Working on privacy and security: differential privacy, encryption, access control
- Building tools for data ingestion and data quality, including medical images
- Benchmarking state-of-the-art methods for accuracy, efficiency and scalability
What they’re looking for
- Taken models to production
- Comfortable with Python, PyTorch/TensorFlow/JAX, Git/GitLab and security of distributed systems
- Experience with federated or distributed learning or with healthcare data is a big plus
- Master's in ML/CS/Data Science or equivalent experience
- English required, commitment to learning French
- Eligibility: open to nationals of CERN Member and Associate Member States
Skills
- Python: Python
- PyTorch: PyTorch
- TensorFlow: TensorFlow
- JAX: JAX
- scikit-learn: scikit-learn
- Git/GitLab: Git, GitLab
- Differential privacy: differential privacy
- Encryption: encryption
- Access control: access control
- Federated learning: federated, federated learning, distributed learning
- Medical images / data ingestion: medical images, data ingestion, data quality
The post
CERN | Machine Learning Engineer | Geneva, Switzerland | HYBRID | Full-time, 3-year contract | From CHF 9,236/month, tax-free
Not a physics job: this role is in CERN's healthcare AI team. CAFEIN, CERN's federated AI platform, trains models on medical data held by hospitals and research institutes across Europe without that data ever leaving them. It powers EU projects such as UMBRELLA and AIM-SAFE.
It's hands-on ML engineering, from experiment to production:
- designing and running ML experiments in Python (PyTorch, TensorFlow, JAX, scikit-learn)
- deploying models on distributed infrastructure shared by several institutions
- privacy and security: differential privacy, encryption, access control
- tools for data ingestion and data quality, including medical images
- benchmarking state-of-the-art methods for accuracy, efficiency and scalability
Looking for an ML engineer who has taken models to production and is comfortable with Python, PyTorch/TensorFlow/JAX, Git/GitLab and the security side of distributed systems. Experience with federated or distributed learning, or with healthcare data, is a big plus. Master's in ML/CS/Data Science or equivalent experience. English required, plus a commitment to learning French.
Eligibility: open to nationals of CERN Member and Associate Member States.
Tax-free salary from CHF 9,236/month, 30 days of leave plus a two-week annual closure, relocation package, health insurance and pension fund. The contract is 3 years, extendable up to 8, with the possibility of applying for an indefinite position.
Apply by 12 December 2026: https://jobs.smartrecruiters.com/CERN/744000161227765-machine-learning-engineer-te-dps-aim-2026-223-ld-