Scientist II Machine Learning Engineer (LLM & GenAI Specialist)

About the role

Owkin is seeking a Scientist II Machine Learning Engineer to design, develop, and deploy advanced AI solutions with a focus on Large Language Models and Generative AI. This role bridges the gap between experimental data science and production-ready systems, requiring collaboration with research and engineering teams to scale models and optimize pipelines. The successful candidate will contribute to the development of scalable machine learning libraries and infrastructure to support biomedical research.

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.

Required skills

• Python
• Deep learning
• PyTorch
• TensorFlow
• Transformer architectures
• Generative AI
• Hugging Face
• Agentic workflows
• RAG
• AWS
• GCP
• Azure
• SageMaker
• Docker
• CI/CD

Nice to have

• Clinical data analysis
• Omics data analysis
• Medical imaging
• Open-source contribution

Qualifications

• Master’s degree in Computer Science, Data Science, or a related quantitative field
• Ph.D. in Computer Science, Data Science, or a related quantitative field

Benefits

• Flexible work organization
• Friendly and informal working environment

About the Company

Owkin is an agentic AI company pioneering Biological Artificial Superintelligence to solve problems in biology. The company builds K Pro, an AI scientist for pharmaceutical research and strategic decision-making, powered by a multimodal patient data network and state-of-the-art AI.