Senior Machine Learning Engineer, Structural Biology | Pharma/BioTech | Series A - Drug discovery B2B Platform | EU Remote | | Salary Up to £130,000K, plus early equity+benefits in Bury

The Client: A leading organization in the drug discovery field is currently looking for a client facing Senior Machine Learning Engineer to drive the development of foundational models that directly impact real-world drug discovery workflows. This hands-on, high-impact role offers the opportunity to advance the application of foundational models to complex structural biology challenges.

The successful candidate will work closely with the leadership team, serving as the technical authority on machine learning modeling, architecture, and experimentation in this domain. While this role does not involve people management, the candidate will be expected to provide mentorship and guidance to engineers and researchers on technical content.

The ideal candidate brings deep expertise in training and deploying state-of-the-art models for protein structure prediction. Beyond technical proficiency, you must understand how these models integrate into broader drug discovery pipelines and possess the strategic mindset needed to break down complex problems into actionable, impactful ML solutions.

• Deep Technical Expertise: Proven experience building and training contemporary models (e.g., AlphaFold, OpenFold, Boltz) at scale in a production environment.
• A strong track record of applying ML to real-world protein structure prediction or drug discovery problems.
• Comfortable in a fast-paced startup environment, with the ability to break down complex technical problems into impactful ML systems.
• Experience in Federated Learning, privacy-preserving ML, or a portfolio of publications in top-tier journals/conferences like NeurIPS, ICML, or Nature Methods.
• Work with our customers and academic partners to define data, preprocessing, selection, and benchmarking strategies for novel training tasks involving protein structures, complexes, and multimodal biological data.
• Carry out case-studies associated with the above, providing scientific and technical expertise to our customers. You will be involved in the full project pipeline, from scoping through to results delivery and dissemination.

• Advance the state-of-the-art by fine-tuning and customizing foundational architectures such as OpenFold, ESMFold, and Boltz-2 for specialized structural biology challenges.
• Architect model extensions tailored for binding affinity and protein complex prediction, overseeing everything from data distillation to rigorous benchmarking.
• Partner with leading academic and industry stakeholders to engineer data selection and preprocessing strategies for complex, multimodal biological datasets.
• Lead comprehensive technical case studies, managing the entire lifecycle from initial project scoping to the final dissemination of results.
• Develop and sustain high-scale ML pipelines that support efficient training, inference, and production-grade deployment.
• Work across internal teams to ensure all model development is anchored in solving genuine drug discovery hurdles.
• Drive external impact through high-quality open-source contributions and scientific publications.

Remuneration: Fully Remote Working Culture, Up to £160,000 Base Salary, Attractive Stock Options, B2B & Full time employee options, Flexible hours + - 3 hours of CET time zone.

If you think you are a good match for the Machine Learning Engineer role, ping us over your CV and we will give you a call if we think you are a good match!