Owkin - Scientist II Machine Learning Engineer (LLM & GenAI Specialist)

Remote - France2w ago

Remote Mid EMEA Genomics Cloud Computing Machine Learning Engineer Learning & Development Medical Records Python Hugging Face MLOps

Requirements

• Education: Master’s or Ph.D. in Computer Science, Data Science, or a related quantitative field with a strong focus on ML/AI. • Education: • Experience: 5+ years of professional experience in software development with Python and a proven track record of deploying deep learning models into production. • ML/DL Frameworks & Ecosystems: Deep understanding of machine learning algorithms, statistical methods, and deep learning frameworks. Mastery of PyTorch or TensorFlow. • ML/DL Frameworks & Ecosystems: • LLM Specialization: Deep understanding of Transformer architectures, attention mechanisms, and the latest breakthroughs in Generative AI. Extensive experience with Hugging Face, with knowledge in agentic workflows and RAG. • LLM Specialization: • Cloud & MLOps: Experience with cloud platforms (AWS, GCP, or Azure) and SageMaker • Cloud & MLOps: • Software Engineering Culture: Strong engineering practices including version control, comprehensive testing, CI/CD, and containerization (Docker). • Software Engineering Culture: • Workflow Optimization: Experience with distributed computing, distributed training strategies for massive datasets, and optimization of ML workflows (e.g., vLLM). • Workflow Optimization: • Domain Expertise: Experience working with clinical or omics data (e.g., genomic sequencing, transcriptomics, electronic health records) and medical imaging processing and analysis. • Domain Expertise: • Contributions to open-source ML projects or research publications. • Collaborative Mindset: Excellent problem-solving skills and the ability to analyze complex technical challenges. • Collaborative Mindset: • Strong communication skills: The ability to explain technical concepts to various stakeholders. • Mentorship: Proactive approach to debugging complex distributed systems, mentoring team members in writing high-quality, maintainable software, and driving a strong technical culture. • Mentorship: • Autonomy: primarily autonomous and capable of being given tasks without excessive detail, able to figure out what to do and execute. • Autonomy:

Responsibilities

• Develop scalable machine learning libraries, tooling, and research workflows in close partnership with research and data scientists. • Shape research infrastructure requirements and drive tool and software choices in collaboration with the platform team. • Champion software engineering best practices across the team, enabling researchers and scientists to write maintainable, testable, efficient, and scalable code. • Design and enhance systems for experiment tracking, reproducibility, and end-to-end model lifecycle management. • Contribute to and accelerate the rapid prototyping of novel models, helping bridge early research and robust implementation.

Benefits

• Flexible work organization • Friendly and informal working environment • Opportunity to work with an international team with high technical and scientific backgrounds • Recruitment Process & Security • Please complete the form and submit your CV.