Machine Learning Developer (EP-CMG-OS-2025-260-GRAP)
CERN European Organization for Nuclear Research
Geneva
Key information
- Publication date:17 December 2025
- Place of work:Geneva
Job summary
Join CERN to innovate in real-time Machine Learning for physics! Enjoy a collaborative environment with exciting challenges and excellent benefits.
Tasks
- Design ML models for CMS Phase-2 Level-1 Trigger selection.
- Integrate ML models into FPGAs for enhanced physics performance.
- Collaborate with teams on ML-for-Trigger research and presentations.
Skills
- Master's or PhD in Physics with relevant professional experience.
- Expertise in Machine Learning and physics data analysis.
- Familiarity with MLOps and FPGA design techniques.
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Job Description
Join us to push the boundaries of real-time Machine Learning (ML) in one of the most demanding computing environments in the world. You will develop cutting-edge ML models for the CMS Level-1 Trigger - an ultra-low-latency, FPGA-based system responsible for selecting the most interesting LHC collisions in real-time.
You will help design the next generation of trigger algorithms for the High Luminosity LHC era by co-training ML models across different systems to maximise physics performance while optimising information flow, bandwidth, and on-device resource usage. This includes developing and scaling MLOps workflows, integrating ML models into FPGAs, and delivering demonstrators that validate full-chain performance from training and physics performance to on-hardware deployment.
This position is part of the NextGen Triggers (NGT) project, a 5-year collaboration between LHC experiments and the CERN Research and Computing Departments. The project leverages innovative Artificial Intelligence technologies and high-performance computing architectures to enhance trigger selection, data processing, and theoretical interpretation for LHC experiments. The insights gained will inform future detector development, data flows, and theoretical tools.
Your responsibilities
- Design and train ML models to boost the physics selections of the CMS Phase-2 Level-1 Trigger by targeting specific signatures and optimising information transport across the multi-algorithm system.
- Develop, deliver, integrate, and test ML models in FPGAs (including RTL/HLS components and software emulators).
- Demonstrate physics performance gains and present results within CMS, at CERN, and at international conferences.
- Design and incorporate MLOps practises, scaling up workflows to ensure reproducible training, validation and deployment of ML-based trigger algorithms.
- Collaborate closely with colleagues in CMS, CERN departments, and external institutes working on ML-for-Trigger research.
Your profile
Experience:
- Experience developing and applying Machine Learning algorithms for physics or scientific data analysis;
- Familiarity with Fast ML / hardware-constrained ML techniques is an advantage;
- Knowledge of physics analysis or physics event reconstruction methods;
- Experience with Trigger and Data Acquisition systems, including hardware architectures;
- Practical experience with software development (e.g. GitHub/GitLab, Continuous Integration, MLOps);
- Basic knowledge of FPGA design including HDLs (VHDL/Verilog) and/or High Level Synthesis (C++);
Skills:
- Machine Learning & Fast Machine Learning;
- Physics Data Analysis & Reconstruction;
- Trigger Systems & Data Acquisition (TDAQ);
- MLOps, Continuous Integration (CI) & CI/CD Pipelines;
- FPGA Design & Programming;
- Hardware Description Languages (HDL) & High-Level Synthesis (HLS);
- Spoken and written English, with a commitment to learn French.
Eligibility criteria:
- You are a national of a CERN Member or Associate Member State .
- You have a professional background in Physics (or a related field) and have either:
- a Master's degree with 2 to 6 years of post-graduation professional experience;
- or a PhD with no more than 3 years of post-graduation professional experience.
- You have never had a CERN fellow or graduate contract before.
Additional Information
Job closing date: 04.02.2026 at 23:59 CET.
Contract duration: 24 months, with a possible extension up to 36 months maximum.
Working hours: 40 hours per week
Job flexibility: Hybrid
Target start date: 01-April-2026
Job reference: EP-CMG-OS-2025-260-GRAP
Field of work: Applied Physics
Benchmark job: 200140 - Applied Physicist
Global Benefits
- A monthly stipend between 6287-6911 Swiss Francs per month (tax free) depending on your degree.
- 30 days of paid leave per year plus 2 weeks annual closure.
- Coverage by CERN’s comprehensive health insurance scheme (for yourself, your spouse and children), and membership of the CERN Pension Fund.
- Family, child and infant monthly allowances depending on your individual circumstances.
- A relocation package (installation grant and travel expenses) depending on your individual circumstances.
- Possibility to extend your contract up to 36 months.
- On-the-job and formal training including language classes.
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