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

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.