Machine Learning Engineer

Job Posting Organization:
CERN, the European Organization for Nuclear Research, is a leading scientific research institution established in 195

• It is known for its groundbreaking work in particle physics and technology, employing over 2,500 staff members and hosting thousands of scientists from around the world. CERN operates in multiple countries and is dedicated to pushing the frontiers of science and technology, fostering an environment of innovation and collaboration.

Job Overview:
The Machine Learning Engineer position at CERN involves contributing to the CAFEIN platform team, focusing on the development of federated AI technologies that are utilized in advanced scientific environments. The role encompasses research and development of state-of-the-art machine learning algorithms, with responsibilities that include designing, implementing, and evaluating these algorithms in various applications such as medical AI, anomaly detection, and complex systems modeling. The engineer will work on large-scale data pipelines and applied solutions, transitioning from exploratory research to deployment. This position also includes supervisory responsibilities, requiring effective communication and collaboration within multidisciplinary teams.

Duties and Responsibilities:
The primary duties of the Machine Learning Engineer include translating real-world challenges into well-defined machine learning problems, designing and implementing ML models using Python and frameworks like PyTorch, TensorFlow, JAX, and scikit-learn. The engineer will contribute to the research and development of federated learning methods and applied ML solutions for various data types, including tabular, image, and signal data. Responsibilities also include performing exploratory data analysis, feature engineering, and visualization to support model development, documenting methods, writing reports, and communicating results effectively within R&D teams. Additionally, the role involves team supervision, ensuring that project goals are met and fostering a collaborative environment.

Required Qualifications:
Candidates must possess a strong background in machine learning, statistics, and data science fundamentals. Proficiency in Python for ML research is essential, along with hands-on experience with major frameworks and libraries such as PyTorch, TensorFlow, JAX, scikit-learn, and Hugging Face. Applicants should have demonstrated experience in designing, implementing, and evaluating advanced ML algorithms, including transformer-based and agentic architectures. Familiarity with federated learning concepts and privacy-preserving ML approaches is advantageous. Strong scientific reasoning and the ability to engage with research literature are also required, along with good communication skills for documentation and collaboration.

Educational Background:
The position requires candidates to have a professional background in Data Science, IT, Mathematics, or a related field. A Master's degree with 2 to 6 years of post-graduation professional experience is required, or a PhD with no more than 3 years of post-graduation experience. Candidates must not have previously held a CERN fellow or graduate contract.

Experience:
The ideal candidate should have a minimum of 2 years of professional experience in machine learning or data science, with a strong emphasis on practical application and experimentation. Experience in conducting ML experiments, benchmarking models, and interpreting results across diverse data modalities is essential. Familiarity with advanced ML techniques and frameworks is also expected.

Languages:
Fluency in spoken and written English is mandatory, with a commitment to learn French being a plus. This bilingual capability will enhance communication within the diverse teams at CERN.

Additional Notes:
The contract duration for this position is 24 months, with the possibility of extension up to a maximum of 36 months. The working hours are set at 40 hours per week, and the position is fully onsite. The target start date is July 1, 202

• The job reference is TE-DPS-AIM-2026-76-GRAP. The compensation includes a monthly stipend ranging from 6372 to 7004 Swiss Francs, which is tax-free, along with 30 days of paid leave per year, comprehensive health insurance coverage, family allowances, and a relocation package depending on individual circumstances. On-the-job and formal training opportunities, including language classes, are also provided.