New comment by lyluo in "Ask HN: Who is hiring? (November 2026)"
- Status
- Open
- Remote policy
- Hybrid
- Employment type
- Not stated
- Salary
- Not stated
- Source
- hn-whoishiring
- First observed
- 2026-11-13 09:57 UTC
- Last seen
- 2026-11-13 09:57 UTC
- Source claims posted
- 2026-11-13 09:04 UTC
- Consecutive misses
- 0 of 10
What the posting says
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-machin...
Quality
- x Salary range stated weight 35%
- + Remote policy stated weight 20%
- x Location stated weight 15%
- + Organisation stated weight 15%
- + Publication date stated weight 15%
Not enough history yet to judge honesty signals.
Timeline
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#1897367 2026-11-13 09:57 UTCPublished