Senior AI Scientist, Biomedical Foundation Models

Boehringer Ingelheim; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

Boehringer Ingelheim is seeking a Staff AI Scientist to join AI Systems in London. You will design and deploy state-of-the-art biomedical foundation models learning from multi-omics, clinical and imaging data to support drug discovery.

The role combines independent research leadership with hands-on model development, mentoring junior scientists and publishing in ML and biomedical AI venues.

Qualifications

• PhD in machine learning, computational biology or related quantitative field with strong publication record.
• Deep understanding of foundation models (transformers) and self-supervised learning.
• Strong software engineering practices with Python and DL frameworks (PyTorch/JAX).
• Experience with distributed training frameworks and large-scale biomedical data processing.
• Ability to translate computational biology questions into research directions for Applied AI and Analytics.
• Experience operating in a matrixed setting as a technical lead.

Responsibilities

• Own and lead significant research workstreams in multimodal biomedical foundation model design across two or more modalities.
• Develop and validate novel learning approaches from biomedical data with reproducible code.
• Design and run rigorous experiments to test model architectures and methods.
• Collaborate with Applied AI teams, computational biologists and human geneticists for downstream applications.
• Mentor Senior AI Scientists and guide experimental designs for independence.
• Publish findings in peer-reviewed ML and biomedical AI venues.

Skills

Transformers

Self-supervised learning

Multimodal data

Research leadership

Education

PhD in ML / Computational Biology

Tools

Python

PyTorch

JAX

Distributed training

Job description

Boehringer Ingelheim is seeking a Staff AI Scientist to join AI Systems in London. You will design and deploy state-of-the-art biomedical foundation models learning from multi-omics, clinical and imaging data to support drug discovery.

The role combines independent research leadership with hands-on model development, mentoring junior scientists and publishing in ML and biomedical AI venues.