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
