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- Tasks: Develop and deploy machine learning models on biological datasets to drive drug discovery.
- Company: Exciting stealth biotech startup revolutionising healthcare with AI.
- Benefits: Competitive salary, equity options, flexible hybrid working, and a collaborative team.
- Why this job: Make a real impact in healthcare while working with cutting-edge technology.
- Qualifications: 4+ years in machine learning, strong Python skills, and experience with biological data.
- Other info: Join a mission-driven team with excellent growth potential and career opportunities.
The predicted salary is between 90000 - 90000 £ per year.
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.
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 use LinkedIn EasyApply.
Bio Machine Learning Engineer in London employer: SR2 | Socially Responsible Recruitment | Certified B CorporationTM
Contact Detail:
SR2 | Socially Responsible Recruitment | Certified B CorporationTM Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Bio Machine Learning Engineer in London
✨Tip Number 1
Network like a pro! Reach out to people in the biotech and machine learning fields on LinkedIn. Join relevant groups and participate in discussions to get your name out there and show off your expertise.
✨Tip Number 2
Prepare for those interviews by brushing up on your technical skills and understanding the latest trends in bioinformatics and machine learning. Practice common interview questions and be ready to discuss your past projects in detail.
✨Tip Number 3
Don’t just apply through job boards; head over to our website and submit your application directly. This way, you can showcase your enthusiasm for the role and stand out from the crowd!
✨Tip Number 4
Follow up after interviews with a thank-you email. It’s a simple gesture that shows your appreciation and keeps you fresh in their minds. Plus, it’s a great opportunity to reiterate your interest in the position!
We think you need these skills to ace Bio Machine Learning Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in machine learning and biological data. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to tell us why you’re the perfect fit for this Bio Machine Learning Engineer role. Share your passion for biotech and how your background can contribute to our mission of accelerating drug discovery.
Showcase Your Technical Skills: We’re looking for strong Python skills and experience with ML frameworks like PyTorch or TensorFlow. Be sure to mention any specific projects where you’ve applied these technologies, especially in a biological context!
Apply Through Our Website: For the best chance of getting noticed, apply directly through our website. It helps us keep track of applications and ensures you’re considered for the role as quickly as possible!
How to prepare for a job interview at SR2 | Socially Responsible Recruitment | Certified B CorporationTM
✨Know Your Tech Inside Out
Make sure you’re well-versed in the machine learning frameworks mentioned in the job description, like PyTorch or TensorFlow. Brush up on your Python skills, especially with libraries like NumPy and Pandas, as you’ll likely be asked to demonstrate your coding abilities.
✨Understand the Biological Context
Since this role involves working with biological datasets, it’s crucial to have a solid grasp of genomics, transcriptomics, and proteomics. Familiarise yourself with relevant tools and pipelines, as this knowledge will help you stand out during discussions about translating experimental data into actionable insights.
✨Showcase Your Collaboration Skills
This position requires working closely with bioinformaticians and lab scientists, so be prepared to discuss your experience in cross-functional teams. Share examples of how you’ve successfully collaborated in the past, particularly in fast-paced environments, to highlight your adaptability and teamwork.
✨Prepare Questions About Their Mission
Demonstrate your genuine interest in the company by preparing thoughtful questions about their AI platforms and drug discovery processes. This shows that you’re not just looking for any job, but are truly invested in their mission to make a real-world impact in healthcare.