What you'll do
ALICE is pioneering the use of GPUs in Run 3 for the online processing and partly for offline reconstruction. To better leverage available GPU compute resources and improve reconstruction performance, we aim to investigate the use of machine learning.
As a GPU and ML software developer, you will maintain, develop, and commission machine-learning-based GPU event reconstruction code for the ALICE experiment, in particular ML-based and ML-supported clusterisation, and track seeding in the ALICE TPC.
In parallel, you will contribute to ALICE’s Monte Carlo production ecosystem and simulation frameworks, focusing on workflow optimisation. This includes the full MC production infrastructure, simulation frameworks, automation of production, validation and integration of ML and GPU-code, and the development and use of intelligent computing tools across the ALICE computing chain.
Your 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.
Still here? Let's make a quick check about
Your profile
- 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.
Your skills
- 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.
Employment conditions
- Participation in a regular stand-by duty, including nights, Sundays and official holidays.
- Stand-by duty, when required by the needs of the Organization.
Global Benefits at CERN
Let's get you ready
Be sure to meet the eligibility criteria
- You are a national of a CERN Member State or Associate Member State. Currently, we cannot consider applications from Pakistani and Lithuanian nationals for positions with a 2026 start date, as the ceiling defined under Article II.5 of the Associate Membership Agreement has been reached.
- 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)
- A copy of your most relevant diploma or a certificate of achievement from your school (if you don't yet have your paper diploma)
- Any document you consider relevant to your application