Machine Learning Engineer

_{16th April, 2026}

ML Engineer
Cambridge – Flexible working arrangements

We are working with a company are working at the forefront of drug development and manufacturing. They turn drugs into useable forms, test them in humans, and manufacture the drugs.

The company are now focused on investing in the Machine Learning and Artificial intelligence space, and have several open positions in the space.
As an AI/ML Engineer, you’ll be involved across the full AI lifecycle – from getting the data in, through to building and deploying models, right through to monitoring how they perform in production.

Internally, you’ll be seen as a go-to technical expert, helping to ensure best practices around responsible AI, model governance, and compliance are followed.

You’ll also work cross functionally with department across the business from product managers, to data engineers, to turn requirements into real-world AI solutions.

Key Responsibilities

• Design, develop, and deploy AI and machine learning models, finetune models as required.
• Build and maintain scalable ML pipelines and infrastructure for classical ML and deep learning.
• Deploy models to production using containerisation, CI/CD, and MLOps toolsets
• Develop LLM-based tools using prompt engineering, retrieval, and embedding pipelines for knowledge retrieval and workflow assistance.
• Embed responsible AI practices, and compliance in all solutions
• Collaborate with cross-functional teams to translate requirements into technical solutions.
• Communicate complex technical concepts in clear terms to technical and non-technical stakeholders.

Ideally you will have

• PhD in relevant field and 2-5 years’ experience in ML / AI engineering, or data science roles.
• Previous experience working with biological or chemical data and understanding of the drug development eco-system
• Proven track record of building, deploying, and maintaining production-grade models
• Strong coding background in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Experience with cloud platforms and ML infrastructure (ideally AWS SageMaker, MLflow).
• Experience with LLMs, vector search, or retrieval-augmented systems.
• Excellent communication skills; able to work cross functionally with stakeholders of both technical and non-technical backgrounds.

This is a great opportunity for someone looking to take the next step in their career, you will get ownership and the chance to help shape a company’s AI and ML strategy. You’ll need to be self-motivated and enjoy the challenge of building things from scratch. Apply today to be considered.