Machine Learning Developer (EP-CMG-OS-2025-260-GRAP), Geneva, Switzerland

What you will do

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 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++).
• Your studies focused on Physics or a related field.

Your 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.

Ideal start date: 01/04/2026
Contract duration: 24 month contract
Job flexibility: Hybrid

Be sure to meet the eligibility criteria

• By the application deadline, you have a master’s degree with 2 to 6 years of professional experience since graduation or a PhD with a maximum of 3 years of professional experience since graduation. You are not eligible with only a bachelor’s degree.
• You have never had a CERN fellow or graduate contract before.
• Please pay attention to the additional criteria and requirements for this specific position and mentioned above.

You will need these documents to complete your application

• Your CV (English or French)
• Any document you consider relevant to your application
• A copy of your most relevant diploma or a certificate of achievement from your school (if you don't yet have your paper diploma)

Your CERN Department

The TE department specializes in maintaining world-class expertise in accelerator technologies, supporting R&D, and managing technical facilities to advance CERN's technological capabilities.

Be prepared with our resources and tips

• Our Hiring Process
• Life at CERN
• Tips for your Application
• Working at CERN
• What happens after you apply?
• More about CERN

How to apply?

See the vacancy here and apply online:

https://careers.cern/jobs/ep-cmg-os-2025-260-grap/

Apply before 04.02.2026. at 23:59 (Geneva Time)



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