Machine Learning Engineer

GenomeKey; Bristol; Hybrid; GBP 55,000 - 75,000; Full time

Job summary

A biotech startup in the UK is seeking a Machine Learning Engineer to develop innovative solutions in antibiotic resistance analysis. The role involves creating machine learning models and collaborating with diverse scientific teams. Candidates should have a Master’s degree or PhD, strong Python skills, and expertise in bioinformatics. Join us to contribute to groundbreaking technologies aimed at preventing treatable infections.

Qualifications

• Expertise in developing ML algorithms for biological data.
• Strong programming skills in Python.
• Experience with large-scale genomic datasets.

Responsibilities

• Develop anomaly-detection models for genomes.
• Collaborate with bioinformatics and microbiology teams.
• Generate and analyse genomic datasets.

Skills

Machine Learning algorithms

Python programming

Bioinformatics workflows

Data integration

Problem-solving

Scientific communication

Education

Master’s degree or PhD in Machine Learning or related field

Tools

PyTorch

TensorFlow

scikit-learn

Job description

Location: Remote with occasional presence at our state of the art labs in Bristol, UK. Approx. once per month.

Start Date: December 2025

Eligibility: Candidates must be eligible to work in the UK to apply for this role. GenomeKey is not able to offer visa sponsorship.

Company

GenomeKey is a Bristol based biotech startup developing a next-generation diagnostic device for bloodstream infections, using machine learning and DNA sequencing.

Within GenomeKey we provide an encouraging environment where knowledge is shared and professional development is supported across both technical and non-technical skillsets.

Join GenomeKey to help build a world where nobody dies from a treatable infection.

Role Responsibilities

We are seeking a constantly curious, creative and skilled Machine Learning Engineer to innovate unique and proprietary machine learning solutions to progress our state of the art antibiotic resistance analysis technologies.

Your Responsibilities Will Include

• Develop bespoke anomaly-detection models for unusual or complex genomes, using state of the art machine learning for genomics.
• Develop, train, and benchmark advanced machine learning models (e.g., masked sequence prediction, transformer-based genome language models) for anomaly detection in bacterial genomes.
• Collaborate with bioinformatics, software engineering, and microbiology teams to ensure seamless integration of ML modules into
• GenomeKey’s genomic analysis platform.
• Analyse and interpret large-scale, proprietary genomic datasets, ensuring robustness, reproducibility, and interpretability of models.
• Support testing and validation by generating and analysing synthetic and real-world datasets.
• Actively engage in knowledge sharing within the development team, wider company and with third parties.
• Contribute to broader activities (e.g., database expansion, statistical frameworks, validation and integration) where technical and domain expertise can add value.

Person Specification

You are passionate about creating and implementing novel algorithms, and developing them into commercial solutions. You enjoy the mathematical and research side of developing new solutions and have enthusiasm for applying fundamental scientific principles to innovative problem solving. You are excited about working within a mixed scientific team of biologists, computer scientists, and engineers to develop new medical technologies.

You have good scientific communication skills, able to share complex ideas at varying levels of technical depth and a desire to work in a startup ecosystem, embracing learning on the job and adapting to new challenges.

Qualifications & Experience

Essential

• Master’s degree or PhD in Machine Learning, Bioinformatics, Computational Biology, or a related discipline (or equivalent industrial experience).
• Demonstrated expertise in developing and applying ML algorithms to biological sequence data, ideally at scale.
• Strong programming skills in Python, with proficiency in ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
• Solid understanding of bioinformatics workflows, including genome assembly, annotation, and QC.
• Experience handling large-scale genomic datasets, including data integration and preprocessing.
• Familiarity with model evaluation, benchmarking, and explainability in applied ML.
• Strong problem-solving skills, with initiative and creativity to tackle novel challenges.
• Excellent communication skills to clearly present technical work to both technical and non-technical audiences.

Desirable

• Hands-on experience with bacterial genomics, plasmid detection, or antimicrobial resistance data.
• Experience with statistical methods for outlier detection (e.g., comparative genomics, codon usage analysis, GC bias).
• Knowledge of anomaly detection, unsupervised learning, or generative modelling applied to genomics.
• Familiarity with transformer-based or language model architectures, especially applied to DNA/protein sequences.
• Prior work in microbial forensics, biosecurity, or clinical diagnostics.
• Exposure to containerised workflows (Docker, RESTful APIs) and deployment in high-performance or cloud environments (AWS/GCP/Azure).
• Awareness of standards and constraints in regulated environments (e.g., ISO 13485, secure air-gapped systems).

We recognise that not every candidate will meet every listed qualification. If you’re excited about this role and believe your background or transferable skills could make you a strong match, we encourage you to apply.

Our Hiring Process

• Intro call with hiring manager (15 minutes)
• Take-home task
• Role-fit interview (45 minutes)
• Final stage interview (45 minutes)

GenomeKey is an equal opportunities employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. If you need any adjustments during the recruitment process, please let us know.