Machine Learning Engineer for Next Generation Triggers (NGT)

Develop and operate CERN’s next-generation machine learning platform to support AI workloads for the High-Luminosity LHC. Work with Kubernetes, GPUs, and cloud-native tools to build infrastructure for machine learning in scientific research.

Responsibilities

• Develop and operate the NGT machine learning platform, covering model training, hyper-parameter optimisation and serving, targeting optimal usage of detector resources.
• Manage cluster resources, integrate new resources, on-premises or via external resources (such as clouds or HPC centers), and optimise resource usage (e.g. via CPU/GPU/RAM affinity layouts) and the existing MLOps workflows to cover deployment, observability and lifecycle management & versioning of models.
• Extend the cloud native infrastructure to support advanced workload scheduling, system monitoring & accounting, as well as prompt cost control.
• Produce and present reference architectures, documentation and best practices to support CERN users and use cases.
• Ensure efficient collaboration with other groups in IT and in other departments, as well as constant alignment with the evolving landscape of external research and industry organisations.

Requirements

• Master's Degree or equivalent relevant experience in the field of Computing Engineering or a related field.
• Knowledge in machine learning systems, ideally with hands-on experience deployment and operating such services in production environments.
• Familiarity with Kubernetes, containerisation, CI/CD, observability and model lifecycle management.
• Experience using GPU and/or other accelerator platforms, including performance tuning and optimisation of inference workloads.
• Familiarity with open-source ecosystems and willingness to contribute, evaluate upstream projects and follow community best practices.
• Enthusiasm for learning new technologies and contributing to cutting-edge scientific computing is essential.
• Knowledge of operating systems.
• Knowledge of system configuration tools.
• Architecture and design of ICT systems.
• Identification and selection of relevant emerging ICT technologies.
• Knowledge and application of software life-cycle tools and procedures.
• Works well in groups and readily fits into a team; participates fully and takes an active role in team activities.
• Addresses complex problems by breaking them down into manageable components.
• Takes initiative beyond regular tasks and makes things happen.
• Shows appreciation for the ideas and contributions of others and encourages others to express their views, even if controversial.
• Spoken and written English, with a commitment to learn French.

Skills

• Machine Learning Systems
• Machine Learning Deployment
• Kubernetes
• Containerisation
• CI/CD
• Observability
• Model Lifecycle Management
• GPU computing
• Inference Workload Optimisation
• Open Source Ecosystems
• Operating Systems
• System Configuration
• IT Architecture
• Emerging Technologies
• Software Life-cycle Tools
• Scientific Computing
• Performance Tuning

Languages

English, French