Senior Machine Learning Engineer - LLM

United Kingdom - London
Posted: 03/02/2026

Salary: £0.00 to £550.00 per Day
ID: 37089_BH

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Senior Machine Learning Engineer

6 Months+ Contract (outside IR35)

Remote



On behalf of a global pharmaceutical organisation, I am seeking a Senior AI/ML Engineer to help design, scale, and deploy advanced machine learning solutions that support the next generation of drug discovery.

You will work closely with AI/ML scientists and life-science experts, transforming exploratory research into robust, production-grade ML pipelines. You will play a pivotal role in strengthening MLOps practices, improving scalability and reliability, and ensuring that innovative ideas deliver real-world scientific impact.

If you are excited by applying AI at scale in a complex scientific environment—and want to help shape the future of AI/ML in the pharmaceutical industry—this could be your next contract!

The Role:

Collaborate directly with AI/ML scientists to optimise models and deploy solutions into production, acting as an internal consultant from prototype to platform. Design and document blueprints and best practices for transitioning research code into scalable, maintainable ML systems. Explore, analyse, and visualise data to understand distributions and identify risks to model performance in real-world deployment. Ensure high data quality and model reliability through data cleaning, validation strategies, and systematic testing. Build and maintain training pipelines and reusable ML components that support scalable, repeatable ML. Contribute to education and upskilling across teams, raising overall MLOps and ML engineering maturity.

Skills/Experience required:

A collaborative, technically strong engineer with a positive mindset and a passion for applied machine learning. PhD or Master's degree with relevant experience, or a Bachelor's degree with strong hands-on expertise. Experience working closely with data scientists, data engineers, and life scientists. Previous experience in a healthcare or life-science organisation is advantageous, but not essential. Excellent communication skills, with the ability to explain complex technical topics to diverse audiences. You will be highly experienced with the following:
Programming & ML tooling: Advanced Python skills; hands-on experience with scikit-learn, Pandas, PyTorch, Jupyter, and ML pipelines. Data & platform tools: Practical knowledge of Databricks, Ray, vector databases, Kubernetes, and workflow orchestration tools such as Apache Airflow, Dagster, or Astronomer. GPU & scalable infrastructure: Experience with GPU computing on-premise and/or in the cloud, including DGX systems or cloud platforms such as AWS (EKS, SageMaker) and Azure (Azure ML, AKS); familiarity with ML platforms like MLflow, ClearML, or Weights & Biases. Cloud & MLOps: Strong understanding of AWS, Azure, containerisation, Kubernetes, DevOps automation, and end-to-end ML lifecycle practices. Data handling: Proven ability to wrangle, process, integrate, and analyse large, heterogeneous datasets, ideally in drug discovery or biomedical contexts. LLMs & generative AI: Experience with large language models, including fine-tuning, pretraining or continued pretraining, inference, RAG pipelines, and multi-agent workflows using tools such as LlamaIndex, LangChain, and vector databases. Production ML: Demonstrated success building, training, and deploying production-grade machine learning models in industry and/or academic research environments.

Please apply online with your CV.

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Senior Machine Learning Engineer - LLM