# Machine Learning Engineer (TE-DPS-AIM-2026-223-LD) at CERN

CERN is hiring a Machine Learning Engineer (TE-DPS-AIM-2026-223-LD) in Geneva, Switzerland. Level rates it Builds AI ●●●●; you can [apply on CERN](https://jobsbylevel.com/go/3451901f-3b9a-440f-9d38-b1d31d60c938?utm_medium=ai-agent).

AI Level 4, AI centrality 95 out of 100. Geneva, GENEVA, Switzerland.

## Details

- Company: [CERN](https://jobsbylevel.com/companies/cern)
- AI level: AI Level 4 (score 95 out of 100)
- Location: Geneva, GENEVA, Switzerland
- Posted: November 12, 2026
- Apply: https://jobsbylevel.com/go/3451901f-3b9a-440f-9d38-b1d31d60c938?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=machine-learning-engineer-te-dps-aim-2026-223-ld-at-cern-3d0920

## Prepare for this job

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## Description

At CERN , the European Organization for Nuclear Research, physicists and engineers are probing the fundamental structure of the universe. Using the world's largest and most complex scientific instruments, they study the basic constituents of matter - fundamental particles that are made to collide together at close to the speed of light. The process gives physicists clues about how particles interact, and provides insights into the fundamental laws of nature. Introduction Help shape the future of healthcare AI, where innovation meets trust. At CERN, you will develop cutting-edge AI solutions that help prevent disease, improve prediction, and deliver trustworthy healthcare insights. You will work on technologies that make it possible to unlock the value of sensitive data without ever moving or exposing it, enabling collaboration where privacy is essential. As part of this role, you will help develop and deploy CAFEIN® , CERN's federated AI platform powering major European healthcare initiatives, including UMBRELLA and AIM-SAFE . You will design advanced federated learning algorithms and secure distributed AI systems that allow models to learn from data across institutions while keeping the data exactly where it belongs. Recognised as a lighthouse example of "data stays, AI collaborates" , CAFEIN® combines state-of-the-art federated learning with CERN's unique strengths in trust, open science, GDPR compliance, and international collaboration. The result is a pioneering framework that is redefining how AI can advance healthcare while safeguarding privacy. Join us to build AI that learns globally, protects locally, and improves lives. Functions Develop and test federated learning software and algorithms. Implement and evaluate privacy-preserving techniques, including differential privacy and homomorphic encryption. Develop tools to optimise data ingestions and assess the quality of data and images. Design and run machine-learning experiments using programming languages like Python with libraries as TensorFLow, PyTorch, or scikit-learn. Analyse data using statistical methods and visualisation for exploratory data analysis (EDA). Implement and benchmark state-of-the-art machine-learning methods, optimising federated learning for utility, communication efficiency, energy use and scalability. Design and deploy Internet of Things (IoT)-based federated learning architectures. Master's degree or equivalent relevant experience in the field of Machine Learning, Computer Science or Data Science or a related field. Experience: Demonstrated experience developing and deploying federated learning solutions in real-world environments. Proficiency in federated learning techniques, including aggregation algorithms, communication and network architecture, security and privacy features. Hands on experience with network security, including certificates, encryption, access control, authorisation, and authentication. Proven experience in coordinating or technically leading machine-learning deployments. Excellent knowledge and hands on experience with software life-cycle tools and procedures (proficiency with Git and GitLab). Excellent knowledge of programming techniques and languages: python, deep learning framework (e.g. TensorFlow, Keras, PyTorch, Jax or scikit-learn). Experience in data analysis in a health care environment would be an asset. Technical competencies: Knowledge and application of software life-cycle tools and procedures. Knowledge of programming techniques and languages. Testing, diagnosing and optimisation of software. Knowledge of best practices for developing secure software. Administration of computing systems, upgrades, application of security patches, system and data migrations, backup and recovery. Behavioural competencies: Achieving Results: delivering high quality work on time and fulfilling expectations. Solving Problems: identifying, defining and assessing problems, taking action to address them. Working in Teams:

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