Senior ML Engineer - LLM & GenAI for Biotech (Remote)

Owkin; Greater London; Remote; GBP 95,000 - 150,000; Full time

Benefits offered by this job

Flexible work organization

Friendly and informal working环境

International team with high technical

Job summary

Owkin in London and Paris seeks a Scientist II Machine Learning Engineer to design, develop, and deploy cutting-edge AI solutions focused on LLMs and Generative AI. You will bridge experimental data science with production ML systems, scaling models and optimizing training and inference pipelines.

You'll collaborate with data scientists and engineers, work with health/omics data, and leverage cloud platforms to deliver robust biomedical solutions.

Qualifications

• Education: Master's or Ph.D. in Computer Science, Data Science, or a related quantitative field with ML/AI focus.
• 5+ years of professional software development experience deploying deep learning models into production.
• Proficiency with PyTorch or TensorFlow and Transformer-based models.
• Extensive experience with LLMs, Generative AI, and RAG workflows.
• Cloud & MLOps experience (AWS, GCP, Azure) and SageMaker; Docker-based CI/CD and containerization.

Responsibilities

• Develop scalable machine learning libraries, tooling, and research workflows with researchers.
• Shape infrastructure requirements and tool choices with the platform team.
• Promote engineering best practices for maintainable, testable, scalable code.
• Design experiment tracking, reproducibility, and end-to-end model lifecycle management.
• Contribute to rapid prototyping of novel models bridging research and production.

Skills

Python

PyTorch

TensorFlow

HuggingFace

Cloud platforms

SageMaker

Docker

CI/CD

Distributed training

Education

Master's or Ph.D. in Computer Science / Data Science

Tools

SageMaker

Docker

Kubernetes

Git

Job description

Owkin in London and Paris seeks a Scientist II Machine Learning Engineer to design, develop, and deploy cutting-edge AI solutions focused on LLMs and Generative AI. You will bridge experimental data science with production ML systems, scaling models and optimizing training and inference pipelines.

You'll collaborate with data scientists and engineers, work with health/omics data, and leverage cloud platforms to deliver robust biomedical solutions.