Machine Learning Engineer

Senior Machine Learning Engineer (LLMs & MLOps) London (Hybrid) Contract 6 Months Rate: Up to £450 per day We are working with a global, research-driven organisation at the forefront of digital innovation within a highly regulated scientific environment. As part of a growing Digital, Data & IT function, they are building advanced AI and machine learning capabilities to transform drug discovery and development. This role is ideal for a Senior ML Engineer with strong LLM experience who enjoys taking models from research notebooks into robust, scalable production environments. The Role You’ll work closely with AI/ML scientists, data engineers and domain experts to optimise, scale and productionise machine learning solutions. The focus is on building end-to-end ML pipelines, enabling real-world deployment of advanced models, including large language models. Key responsibilities include: • Partnering with ML scientists to transition prototypes into production-ready systems • Designing and building scalable ML training and inference pipelines • Developing and maintaining MLOps best practices and reusable components • Exploring, analysing and visualising complex datasets to identify data quality and performance risks • Ensuring data quality through validation, cleaning and monitoring strategies • Supporting and upskilling teams on ML engineering and MLOps practices Required Experience • Strong commercial or research experience as an ML Engineer or AI Engineer • Advanced Python skills and experience with ML frameworks (e.g. PyTorch, Scikit-learn, Pandas, Jupyter) • Hands-on experience with LLMs, including fine-tuning, inference, RAG and multi-agent workflows (e.g. LangChain, LlamaIndex, vector databases) • Experience building production-grade ML systems • Familiarity with ML platforms and tooling (e.g. MLflow, Weights & Biases, ClearML) • Experience with cloud platforms (AWS and/or Azure) and containerised environments (Kubernetes) • Exposure to workflow orchestration tools such as Airflow, Dagster or Astronomer • Experience working with large, heterogeneous datasets Nice to Have • GPU computing experience (on-prem or cloud) • Background in healthcare, life sciences or research-heavy environments • MSc or PhD in a relevant technical discipline What’s on Offer • High-impact role within a fast-growing AI and digital function • Work on cutting-edge ML and LLM use cases with real-world impact • Collaborative, inclusive culture with strong emphasis on innovation and learning