Machine Learning Engineer - Automated Chromatography Analysis (EFT)

Eurofins Scientific is an international life sciences company, providing a unique range of analytical testing services to clients across multiple industries, to make life and our environment safer, healthier and more sustainable. From the food you eat, to the water you drink, to the medicines you rely on, Eurofins laboratories work with the biggest companies in the world to ensure the products they supply are safe, their ingredients are authentic, and labelling is accurate. Eurofins is dedicated to delivering testing services that contribute to the health and safety of society and the planet, and to its corporate responsibility to protect the environment and ensure diversity, equity, and inclusion across the entire network of Eurofins companies. We are seeking a Machine Learning (ML) Expert with experience in chemical data processing to drive AI innovations in analytical chemistry. You will design and deploy Machine Learning solutions for GC-MS, and HPLC-MS, data, working alongside scientists and engineers to extract valuable insights from complex datasets. Job Duties: Develop AI/ML models for processing mass spectrometry and chromatography data Build software solutions to automate chemical data analysis and interpretation Integrate ML algorithms into analytical pipelines for chemical property prediction and anomaly detection Optimize data structures for high-throughput chemical analysis Collaborate with data scientists Troubleshoot complex technical issues and optimize software performance Additional duties as assigned Basic Minimum Qualifications: MSc or PhD in Machine Learning, Data Science, Chemistry, or a related field Strong programming skills in Python (Pandas, Scikit-learn, PyTorch, TensorFlow) Experience with, GC-MS, HPLC-MS and handling large chemical datasets Familiarity with cloud-based AI solutions (AWS, Azure, GCP) Authorization to work in the United States without restriction or sponsorship Ideal Candidate will have: Experience with Docker, Kubernetes