GPU & ML Developer for Reconstruction and Simulation

As a GPU and ML software developer, you will maintain, develop, and commission machine-learning-based GPU event reconstruction code for the ALICE experiment, focusing on ML-based clusterisation and track seeding in the ALICE TPC. You will also contribute to Monte Carlo production ecosystem and simulation frameworks, optimizing workflows and integrating ML and GPU code.

Responsibilities

• Commission the GPU TPC ML clusterisation as the default clusterisation code for data taking and for simulation.
• Benchmark and improve the ML-based clusterisation in terms of processing performance and physics quality.
• Investigate extending ML usage, including to TPC track seeding.
• Contribute to the Monte Carlo production ecosystem, including workflow scheduling, multi-timeframe processing, multi-threading, and integration of ML/GPU components.
• Develop and operate automated solutions for MC production, job orchestration, and validation, including ML-based anomaly detection.
• Track the activities in the optimisation and modernisation of simulation and reconstruction frameworks (e.g. Geant, AliceO2), including ML-driven acceleration and GPU-based approaches.
• Investigate components and algorithms of the ALICE computing chain (simulation, reconstruction, etc.) that could benefit from machine learning and develop prototypes.

Requirements

• You are a national of a CERN Member State or Associate Member State, excluding Pakistani and Lithuanian nationals for 2026 start date.
• 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.
• Experience with high energy physics (HEP) experiments event reconstruction code (e.g. clusterisation or tracking).
• Experience with GPU programming and ML training and inference.
• Practical experience with debugging large distributed applications.
• Your studies focused on Physics.
• Strong knowledge of the C++ programming language on Linux.
• Knowledge of at least one GPU programming toolkit such as CUDA or HIP.
• Knowledge of an ML framework such as ONNXRuntime.
• Knowledge of debugging tools such as GDB and profiling tools such as perf.
• Ability to work in a team.
• Spoken and written English, with a commitment to learn French.

Skills

• GPU Programming
• Machine Learning Training
• Machine Learning Inference
• High Energy Physics Reconstruction
• C/C++ Programming
• linux
• CUDA
• HIP
• ONNXRuntime
• Debugging Distributed Applications
• GDB
• Performance Profiling
• Monte Carlo Simulation
• Process Optimization
• Event Reconstruction
• Clusterisation
• Track Seeding

Languages

English