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# ML Engineer

- **Company:** Responsibilitiescontribute
- **Location:** London, UK
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Artificial Intelligence, Computational Biology, Distributed Computing Environment, Python (Programming Language), Machine Learning, Open Source Technology, Pytorch, Deep Learning, Information Technology, Machine Learning Operations, Software Version Control
- **Published:** September 25, 2026
- **Apply:** https://www.apply4u.co.uk/jobs/ml-engineer/48275238

## About the Role

PhD preferred or MSc with equivalent industry experienceHands-on experience with deep learning and foundation model implementations such as transformers, pre-training and fine-tuningSome experience contributing to production-quality model artefacts, with a growing understanding of what is required to move from research prototypes to reliable deploymentExperience collaborating with researchers during the implementation processProficiency in Python and deep learning frameworks such as PyTorchStrong software engineering fundamentals such as writing clean, testable, well-documented and maintainable code, version control, code reviewsWorking knowledge of distributed training frameworks such as PyTorch Distributed, DeepSpeed, FSDP or Ray TrainExposure to model optimisation techniques for inference, e.g. quantisation, distillation, pruningPreferred QualificationsExperience working with biomedical data modalities such as genomics, multi-omics, clinical or imaging data in an ML
context is advantageousPublications or contributions to open-source ML projects or toolingThis is a hybrid role with approximately 3 days a week in the officeWHY THIS IS A GREAT PLACE TO WORKBoehringer Ingelheim has been recognised as aTop Employer in the UK, demonstrating our commitment to building an exceptional workplace through strong people practices and supportive HR policies.To learn more about why BI is a great place to work, visit: #J-18808-Ljbffr

## Description

medical imaging to support patient segmentation. It could be 'omics data to identify novel therapeutic targets. It could be predicting transcriptional change for a given disease-causing variant. It could be simulating the effect of modulating a target of interest.A core component of the AI Accelerator is AI Systems, a team focused on designing, building and deploying multimodal foundation models across the vast biomedical data landscape that will be used within Computational Innovation to enhance and accelerate portfolio decision-making.THE POSITIONWe are looking for an ML Engineer to join the AI Systems team and contribute to work at the frontier of biomedical AI. This is a hands-on engineering role with real stakes, as the models you help build will be used to make decisions about which indications to pursue, in which patient population and against which target.You will work in close partnership with AI scientists and more experienced ML engineers, supporting the translation of, tokenisers, inference logic and fine-tuning interfaces to a high engineering standardWork closely with AI scientists to help translate validated research prototypes into robust, production-quality model artefacts, and contribute to benchmarking and performance evaluationContribute to the optimisation of validated models and inference pipelines, applying techniques such as quantisation, distillation and pruning to help meet production efficiency and latency requirements without compromising model performanceWrite clean, well-tested, well-documented code and follow the engineering standards set by the teamSupport model handovers to MLOps engineers, contributing documentation covering capabilities, known limitations, failure modes and retraining criteriaStay current with advances in ML engineering, distributed training and biomedical AI toolingRequired QualificationsPostgraduate degree in Machine Learning, Computer Science, Computational Biology or a related technical field


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