Machine Learning Engineer

Machine Learning EngineerLocation: Remote-firstType: Full-time, permanentSalary: £70,000 - £100,000 + benefitsAbout the CompanyThis BioAI startup is developing next-generation diagnostic technologies for bloodstream infections using cutting-edge machine learning and DNA sequencing. The team combines expertise across genomics, microbiology, and data science to accelerate how infectious diseases are detected and treated.Having built a strong foundation in both lab and data infrastructure, the company is now expanding its compsci team with a focus on developing advanced ML models for genomic analysis - work that directly contributes to saving lives through faster, more accurate diagnosis.The RoleWe’re hiring a Machine Learning Engineer to lead the development of a bacterial genome anomaly detection system - building bespoke algorithms that identify unusual patterns in genomic data and support the company’s mission to prevent incorrect antibiotic prescriptions.You’ll design and test novel ML methods using foundational pre-trained genomic embeddings and custom anomaly-detection architectures, turning proprietary data into interpretable, high-impact models.This is a deep research role: success will come through rapid iteration, creativity, and scientific curiosity rather than polished productisation.It’s well suited to someone who thrives in a small, autonomous team, enjoys experimental algorithm development, and wants their work to have measurable real-world impact.What You’ll DoDesign and implement bespoke anomaly-detection models for bacterial genomesDevelop, train, and benchmark transformer-based and foundation-model approaches for genome representationConduct rapid, iterative research, evaluating ideas through experiments rather than long production cyclesCollaborate with bioinformatics, microbiology, and software teams to integrate models into GenomeKey’s diagnostic pipelineAnalyse large-scale proprietary genomic datasets to ensure model robustness and interpretabilityGenerate and evaluate synthetic and real-world data for validationShip prototype code to third-party partners for testing and feedbackContribute to broader R&D initiatives such as statistical framework design and data infrastructure developmentWhat We’re Looking ForRequiredMSc or PhD in Machine Learning, Computational Biology, Bioinformatics, or related discipline (or equivalent industry experience)Demonstrated ability to apply ML methods to biological or genomic dataStrong Python skills with experience in PyTorch, TensorFlow, or scikit-learnUnderstanding of bioinformatics workflows (e.g. genome assembly, QC, annotation)Experience working with large or complex genomic datasetsFamiliarity with model evaluation, benchmarking, and explainabilityAbility to work autonomously, design experiments, and iterate quicklyStrong communication skills for cross-functional collaborationWhy Join?Work on a genuinely novel problem - genomic anomaly detection for clinical diagnosticsCombine academic-level research with startup agility and real-world impactAutonomy to explore and build new ML algorithms from first principlesJoin a collaborative, science-driven team that values experimentation and creativityContribute to technology that could change how bacterial infections are diagnosed worldwide