Machine Learning Engineer

Machine Learning EngineerLocation: 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 ForRequired

• 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