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Machine Learning Developer (EP-CMG-OSGRAP)
Machine Learning Developer (EP-CMG-OSGRAP)CERN • Geneva, Geneva, Switzerland
Machine Learning Developer (EP-CMG-OSGRAP)

Machine Learning Developer (EP-CMG-OSGRAP)

CERN • Geneva, Geneva, Switzerland
Il y a plus de 30 jours
Description de poste

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 Masters 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-OSGRAP

    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 CERNs 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.
  • Overview of CERN - Discover a world where the impossible is made possible!

    At CERN the European Organization for Nuclear Research we are pushing the frontiers of science and technology. Our groundbreaking work brings together not only physicists but also a diverse range of professionals from engineering technical scientific and administrative fields. Together we foster an environment where innovation and collaboration thrive.

    Every day we face exciting new challenges and opportunities to contribute to cutting-edge research that shapes our understanding of the universe. We meet these challenges through the diverse perspectives within our teams ensuring every contribution is valued and driving our shared sense of inclusion and purpose. Diversity is a core value of CERN since its foundation and it remains central to our mission and continued success.

    If you are ready to be part of a dynamic inclusive community pushing the boundaries of knowledge CERN is the place where your curiosity and skills can thrive. Be part of our mission to uncover what lies at the heart of the universe!  TAKE PART!

    More information about us here :

    Remote Work :

    No

    Employment Type : Full-time

    Key Skills

    Industrial Maintenance,Machining,Mechanical Knowledge,CNC,Precision Measuring Instruments,Schematics,Maintenance,Hydraulics,Plastics Injection Molding,Programmable Logic Controllers,Manufacturing,Troubleshooting

    Experience : years

    Vacancy : 1

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