Senior ML Engineer: Biomedical Foundation Models (Hybrid)

Kemioconsulting; Greater London; Hybrid; GBP 90,000 - 140,000; Full time

Job summary

Kemioconsulting is seeking a Senior ML Engineer to design, implement and productionize large-scale biomedical foundation models in a hybrid London setting. You will collaborate with AI Scientists to translate cutting-edge research into robust software used across the organization.

The role focuses on scalable training pipelines, efficient model architectures and deployable inference services, fueling biomedical AI initiatives with strong engineering discipline.

Qualifications

• PhD in Machine Learning, Computer Science, Computational Biology or similar.
• Plus 3-6 years of post-study work experience, working with biomedical datasets such as omics, clinical or imaging data.
• Strong experience developing deep learning models and foundation model architectures, including transformers, pre-training and fine-tuning.
• Excellent Python programming skills and experience with frameworks e.g., PyTorch or JAX.
• Strong software engineering fundamentals, including testing, documentation, code reviews and version control.
• Experience with distributed training technologies such as PyTorch Distributed, DeepSpeed, FSDP or Ray Train.
• Experience working alongside research scientists to deliver production machine learning systems.

Responsibilities

• Partner with AI Scientists to transform validated research into production-ready machine learning systems.
• Contribute to the architecture and implementation of large-scale foundation models, ensuring they are efficient, scalable and deployment-ready.
• Develop high-quality training pipelines, data loaders, tokenisation frameworks, inference services and fine-tuning workflows.
• Build clean, maintainable and thoroughly tested Python code following software engineering best practices.
• Benchmark and evaluate model performance while helping optimise training efficiency and scalability.
• Collaborate closely with MLOps teams to ensure smooth deployment, documentation and ongoing model maintenance.
• Produce comprehensive technical documentation covering model capabilities, limitations and retraining strategies.
• Stay up to date with emerging developments in machine learning engineering, distributed training and biomedical AI.

Skills

Deep learning

Foundation models

Python

Distributed training

Software engineering

Team collaboration

Education

PhD in ML/CS/Computational Biology

Tools

PyTorch

JAX

DeepSpeed

FSDP

Ray Train

Job description

Kemioconsulting is seeking a Senior ML Engineer to design, implement and productionize large-scale biomedical foundation models in a hybrid London setting. You will collaborate with AI Scientists to translate cutting-edge research into robust software used across the organization.

The role focuses on scalable training pipelines, efficient model architectures and deployable inference services, fueling biomedical AI initiatives with strong engineering discipline.