Job Specifications
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
About the Company
We believe that advanced technology is paving the way to a more sustainable future.
We believe in going the extra mile to provide our customers with a competitive edge.
Since our inception in 2010, Cubiq has established a reputation for excellence in the delivery of high quality engineering talent to the most ground-breaking technology companies in the world.
Cubiq methods are subtle, data-driven, and highly effective, which is how we have become widely recognised as leading experts within engineering and technology recr...
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