Machine Learning Engineer - AI Drug Discovery

CT19 is partnering with an innovative AI-driven drug discovery company that is building advanced machine learning solutions for drug discovery.

Having established a strong customer base across biotech and pharma, they are now looking to hire a Research Engineer to help scale its machine learning capabilities and contribute to the next generation of computational drug discovery tools.

This is an opportunity to join a highly technical, multidisciplinary team working at the intersection of machine learning, chemistry, biology and software engineering. You'll play a key role in developing production-grade ML systems, supporting scientific innovation, and helping deliver impactful solutions used by researchers worldwide.

The role:

As a Research Engineer, you will be responsible for developing and deploying machine learning solutions that support molecular design and drug discovery workflows. You will work closely with scientists, engineers and end users to transform cutting-edge research into robust, scalable products.

Key Responsibilities:

• Develop and optimise machine learning models for molecular property prediction and related scientific applications
• Expand and maintain automated model development and evaluation workflows
• Build and improve ML infrastructure, including training pipelines, experiment tracking, model registries and deployment processes
• Curate, validate and prepare scientific datasets for model development
• Collaborate with cross-functional teams to design and deliver user-focused solutions
• Contribute to technical documentation, publications and presentations where appropriate
• Support the ongoing evolution of engineering standards, tooling and best practices

What we are looking for:

• Commercial experience building and deploying machine learning systems in production environments
• Strong software engineering fundamentals and coding skills
• Experience with MLOps tooling, experiment tracking, model serving and containerisation technologies
• Exposure to cloud platforms such as AWS, GCP or Azure
• Familiarity with infrastructure-as-code approaches and modern development workflows
• Strong communication skills with the ability to collaborate across technical and scientific disciplines

Nice to have:

• Experience working with molecular, chemical or biological datasets
• Exposure to computational chemistry, cheminformatics or drug discovery applications
• Contributions to open-source scientific or machine learning software projects
• PhD or advanced degree in Chemistry, Computational Chemistry, Computer Science, Machine Learning or a related discipline

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