London Biomedical AI Systems Engineer

Boehringer Ingelheim GmbH; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Boehringer Ingelheim GmbH in London is seeking an ML Engineer to join the AI Systems team. You will help translate validated research into production-ready models and contribute to scalable training and inference pipelines.

You will collaborate with AI scientists and other ML engineers to ensure production-quality artefacts, with an emphasis on efficiency, scalability, and rigorous engineering standards. This hybrid role requires 3 days in the office.

Qualifications

• Postgraduate degree in Machine Learning, Computer Science, Computational Biology or related field; PhD preferred or MSc with equivalent industry experience.
• Hands-on experience with deep learning and foundation model implementations such as transformers, pre-training and fine-tuning.
• Some experience contributing to production-quality model artefacts, moving from research to deployment.
• Experience collaborating with researchers during implementation.
• Proficiency in Python and PyTorch.
• Strong software engineering fundamentals: clean, tested, well-documented code, version control, reviews.
• Knowledge of distributed training frameworks such as PyTorch Distributed, DeepSpeed, FSDP or Ray Train.
• Exposure to model optimisation techniques for inference (quantisation, distillation, pruning).

Responsibilities

• Contribute engineering perspectives to architectural design discussions to ensure scalable foundation models for training and inference.
• Under supervision, implement biomedical foundation model components like training code, data loaders, tokenisers, and inference logic to a high standard.
• Collaborate with AI scientists to translate validated research prototypes into production-ready model artifacts and benchmarks.
• Optimise validated models and inference pipelines to meet production latency and efficiency requirements.
• Write clean, well-tested, well-documented code and adhere to team engineering standards.
• Contribute to model handovers to MLOps engineers with documentation on capabilities, limitations, and retraining criteria.
• Stay updated on advances in ML engineering and biomedical AI tooling.

Skills

Python

PyTorch

Deep learning

Distributed training

Software engineering

MLOps

Model optimisation

Education

Postgraduate degree in ML/CS/Computational Biology

Tools

PyTorch Distributed

DeepSpeed

FSDP

Ray Train

Job description

Boehringer Ingelheim GmbH in London is seeking an ML Engineer to join the AI Systems team. You will help translate validated research into production-ready models and contribute to scalable training and inference pipelines.

You will collaborate with AI scientists and other ML engineers to ensure production-quality artefacts, with an emphasis on efficiency, scalability, and rigorous engineering standards. This hybrid role requires 3 days in the office.