In ~1 minute you get: who interviews you, the likely questions answered from your CV, and your CV tailored to this job. Your first dossier is free.

About us Owkin is an agentic AI company pioneering Biological Artificial Superintelligence to solve problems in biology where human researchers alone have failed. Owkin builds K Pro - an AI scientist for pharmaceutical research and strategic decision-making. K Pro orchestrates a suite of AI skills and tools to decode complex biology, accelerate research, and dramatically increase productivity. K Pro is built on Owkin’s unrivalled multimodal patient data network, state-of-the-art AI for biology and a decade of experience working with pharmaceutical partners. Position is based in our Paris offices or remotely in France, UK, or Germany. About the role: We are seeking a highly skilled and experienced Scientist II Machine Learning Engineer to design, develop, and deploy cutting-edge AI solutions. In this role, you will focus heavily on Large Language Models (LLMs), Generative AI, and Advanced Deep Learning architectures. You will bridge the gap between experimental data science and production-ready ML systems. Working closely with our Data Science and Engineering teams, you will scale complex models, optimize training and inference pipelines, and leverage cloud ecosystems to deliver robust biomedical solutions. Experience handling health, clinical, or omics data (genomics, transcriptomics, proteomics, etc.) is a major plus. In particular, you will: 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. Other Ad-hoc responsibilities, tasks and projects assigned by the management. D. in Computer Science, Data Science, or a related quantitative field with a strong focus on ML/AI. 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. 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. Cloud & MLOps: Experience with cloud platforms (AWS, GCP, or Azure) and SageMaker Software Engineering Culture: Strong engineering practices including version control, comprehensive testing, CI/CD, and containerization (Docker). , vLLM). , genomic sequencing, transcriptomics, electronic health records) and medical imaging processing and analysis. Contributions to open-source ML projects or research publications. Soft skills and culture add: Collaborative Mindset: Excellent problem-solving skills and the ability to analyze complex technical challenges. 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.

Scientist II Machine Learning Engineer (LLM & GenAI Specialist)

Don't apply unprepared

Scientist II Machine Learning Engineer (LLM & GenAI Specialist)

Don't apply unprepared