Machine Learning Engineer / Drug Discovery / £100k + Equity

AI is transforming drug discovery... but there’s a problem.

Most models are built on sparse, fragmented, and low-quality data.

So instead of accelerating breakthroughs, they often lead to dead ends.

We’re working with a cutting-edge, seed-stage start-up building an AI-native platform powered by deeply curated, high-quality experimental molecular data, unlocking better predictions across potency, binding, and ADMET.

Their platform is already used by hundreds of chemists globally, directly impacting real-world programs across oncology, neurodegeneration, inflammation, and global health.

Now, they’re hiring a Founding Machine Learning Engineer to help define the future of AI-driven drug design.

⭐️What you’ll be doing⭐️

• Building state-of-the-art models for molecular property prediction, including foundation models and AutoML pipelines
• Designing and scaling ML infrastructure (training pipelines, experiment tracking, model registry, CI/CD)
• Deploying low-latency, production-grade model serving systems
• Developing robust data pipelines for dataset curation, validation, and versioning
• Working closely with scientists, product teams, and users to ship impactful features

⭐️What we’re looking for⭐️

• 3+ years building and deploying ML systems in production (not just research)
• Strong software engineering fundamentals
• Experience with MLOps tooling, model serving, and containerisation
• Comfortable working with cloud infrastructure (AWS, GCP, or Azure)
• High ownership mindset with the ability to operate in ambiguity

⭐️Nice to have⭐️

• Background in computational chemistry, physics, or related fields
• Contributions to open-source ML or scientific tooling
• Experience deploying ML systems at scale

If this sounds interesting, even if you do not meet all of the requirements, please apply with your CV attached.