Machine Learning Engineer
3 days ago
City of London
Machine Learning Engineer Location: Remote-first Type: Full-time, permanent Salary: £70,000 - £100,000 + benefits About the Company This 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 Role We’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 Do • Design and implement bespoke anomaly-detection models for bacterial genomes, • Develop, train, and benchmark transformer-based and foundation-model approaches for genome representation, • Conduct rapid, iterative research, evaluating ideas through experiments rather than long production cycles, • Collaborate with bioinformatics, microbiology, and software teams to integrate models into GenomeKey’s diagnostic pipeline, • Analyse large-scale proprietary genomic datasets to ensure model robustness and interpretability, • Generate and evaluate synthetic and real-world data for validation, • Ship prototype code to third-party partners for testing and feedback, • Contribute to broader R&D initiatives such as statistical framework design and data infrastructure development What We’re Looking For Required • MSc 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 data, • Strong Python skills with experience in PyTorch, TensorFlow, or scikit-learn, • Understanding of bioinformatics workflows (e.g. genome assembly, QC, annotation), • Experience working with large or complex genomic datasets, • Familiarity with model evaluation, benchmarking, and explainability, • Ability to work autonomously, design experiments, and iterate quickly, • Strong communication skills for cross-functional collaboration Why Join? • Work on a genuinely novel problem - genomic anomaly detection for clinical diagnostics, • Combine academic-level research with startup agility and real-world impact, • Autonomy to explore and build new ML algorithms from first principles, • Join a collaborative, science-driven team that values experimentation and creativity, • Contribute to technology that could change how bacterial infections are diagnosed worldwide
