Machine Learning Research Engineer/ScientistS3 Science Recruitment • London, England, United Kingdom
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Machine Learning Research Engineer/Scientist
S3 Science Recruitment
- London, England, United Kingdom
- London, England, United Kingdom
About
As an
Applied Machine Learning Engineer / Scientist , you will apply and adapt state-of-the-art machine-learning models to real-world problems in drug discovery and molecular design. You will work on applied projects in close collaboration with external partners, focusing on tailoring advanced models to specific scientific objectives. Your role will involve translating partner and internal research needs into concrete modelling strategies. This includes curating and adapting datasets, selecting and tuning model architectures and objectives, running experiments, and iterating rapidly to maximise performance in applied settings. You will own the full applied modelling lifecycle, from problem formulation and experimentation through evaluation and delivery. You will also contribute insights from applied work back into core model development, helping identify gaps, limitations, and opportunities for improvement in foundational models based on real-world usage. This role suits someone who enjoys operating at the intersection of cutting-edge ML and practical deployment — a technically strong, execution-focused scientist or engineer motivated by turning advanced models into reliable, high-impact tools. About you
Strong hands-on experience applying machine-learning methods to real-world problems Experience working with biological, chemical, or molecular datasets Strong proficiency with PyTorch and the scientific Python ecosystem (e.g. NumPy, SciPy, Pandas) Experience contributing to and maintaining high-quality deep-learning codebases, with attention to reproducibility, testing, and engineering standards Experience collaborating with external partners or stakeholders, translating scientific questions into concrete modelling and evaluation approaches Publication record in machine learning or life-science venues, particularly where research was driven by applied or translational goals Experience working in interdisciplinary environments spanning ML, biology, chemistry, and related fields What’s on offer
Opportunity to deliver real-world impact by building tools used by scientists across industry and academia Collaboration within a highly skilled, multidisciplinary technical and scientific team Significant ownership and autonomy across applied modelling projects Competitive compensation package, including meaningful equity participation
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Languages
- English
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