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