Bio Machine Learning Engineer

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.