Job Title: Bio Machine Learning Engineer
Location: Near London (Hybrid, 2 days onsite)
Salary: Up to £90,000
Company: Stealth Biotech Startup (Series A)
About the Company
This early-stage biotech startup is building next-generation AI platforms to accelerate drug discovery and precision medicine. Backed by top-tier VC, they combine cutting-edge machine learning with experimental biology to unlock new therapeutic pathways across oncology and rare diseases.
Their team works across computational biology, machine learning, and wet-lab science -working closely to turn complex biological data into real-world clinical impact.
The Role
They are looking for a Bio Machine Learning Engineer to help design and deploy models that make sense of high-dimensional biological data. The successful candidate will work alongside bioinformaticians, software engineers, and lab scientists to build scalable ML systems that directly influence the discovery pipeline.
This is a hands-on role with ownership - from prototyping models to productionising them in a fast-moving start-up environment.
What You’ll Be Doing
- Develop and deploy machine learning models on biological datasets (e.g. genomics, transcriptomics, proteomics)
- Build pipelines for processing and analysing large-scale biological data
- Apply deep learning techniques (e.g. transformers, graph neural networks) to biological problems
- Collaborate with wet-lab teams to translate experimental data into actionable insights
- Optimise models for performance, scalability, and real-world usability
- Contribute to the design of their ML infrastructure and tooling stack
What They’re Looking For
- 4+ years experience in machine learning, data science, or AI engineering
- Strong Python skills (NumPy, Pandas, PyTorch/TensorFlow)
- Experience working with biological or biomedical data (industry or academia)
- Solid understanding of ML fundamentals (supervised/unsupervised learning, model evaluation, etc.)
- Familiarity with cloud platforms (AWS, GCP, or Azure)
- Ability to work in a cross-functional, fast-paced startup environment
Nice to Have
- Background in bioinformatics, computational biology, or related field
- Experience with genomics pipelines or tools (e.g. FASTQ, BAM, variant calling)
- Knowledge of protein structure modelling or drug discovery workflows
- Exposure to MLOps, deployment, and production systems
- Publications or open-source contributions in relevant domains
Why Join Them
- Opportunity to work on genuinely impactful problems in healthcare and life sciences
- Early-stage equity with strong growth potential
- Collaborative, mission-driven team with deep technical expertise
- Flexible hybrid working (London / Cambridge)
- Chance to shape both the product and engineering culture
How to Apply
For more information or to apply, please get in touch with me or used LinkedIn EasyApply.