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- Tasks: Lead the development of machine learning systems for drug discovery.
- Company: Early-stage biotech startup in Oxford with a mission to revolutionise therapy development.
- Benefits: Competitive salary, equity options, and a chance to shape the future of healthcare.
- Other info: Join a small, elite team with high autonomy and growth potential.
- Why this job: Make a real-world impact by contributing to therapeutic discoveries.
- Qualifications: Strong ML background, experience in life sciences, and proficiency in Python.
The predicted salary is between 100000 - 120000 £ per year.
I'm working with an early-stage biotech startup based in Oxford building machine learning-driven platforms for drug discovery. Their mission is to dramatically reduce the time and cost of bringing new therapies to market by combining computational biology, large-scale biological datasets, and modern ML techniques. Backed by top-tier investors, they're a small, high-calibre team of scientists and engineers.
We're hiring a Lead Bio-ML Engineer to take ownership of our core machine learning systems. This is a high-impact, high-autonomy role where you'll:
- Own the end-to-end ML lifecycle (data, modelling, deployment)
- Work closely with biologists to translate experimental problems into ML solutions
- Build and scale models across areas like sequence modelling, structure prediction, and multimodal biological data
- Shape the technical direction and ML roadmap
- Mentor and grow a small team as they scale
What You'll Do:
- Designing models for genomics, proteomics, and drug discovery pipelines
- Applying deep learning / foundation models to biological datasets
- Building robust, production-ready ML systems (not just research prototypes)
- Developing internal tooling for data pipelines, experiment tracking, and model evaluation
Core experience:
- Strong background in machine learning / AI engineering
- Experience applying ML to life sciences, bioinformatics, or computational biology
- Production experience with Python + PyTorch / TensorFlow
- Track record of owning and shipping ML systems end-to-end
Nice to have:
- Experience with biological data (e.g. sequencing, protein structures)
- Familiarity with drug discovery or wet-lab collaboration
- Exposure to LLMs / foundation models in biology
- Previous startup or high-ownership environment
High ownership: you'll define and build critical systems from the ground up. Real-world impact: your work directly contributes to therapeutic discovery. Tight feedback loop: collaborate daily with domain experts. Equity upside: meaningful stake in an early-stage company. Small, elite team: no bureaucracy, just execution.
Please apply here or reach out to me directly on LinkedIn/ via email (adam.lockett@sr2rec.co.uk).
Lead Bio Machine Learning Engineer in Oxford 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 Lead Bio Machine Learning Engineer in Oxford
✨Tip Number 1
Network like a pro! Reach out to people in the biotech and machine learning fields on LinkedIn. Join relevant groups and engage in discussions to get your name out there and show your passion for the industry.
✨Tip Number 2
Prepare for interviews by brushing up on your technical skills and understanding the latest trends in bioinformatics and ML. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with biologists and other team members.
✨Tip Number 3
Showcase your projects! Whether it's a GitHub repo or a portfolio, make sure you have tangible examples of your work ready to share. This will help demonstrate your hands-on experience and problem-solving abilities in real-world scenarios.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our awesome team at StudySmarter.
We think you need these skills to ace Lead Bio Machine Learning Engineer in Oxford
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Lead Bio-ML Engineer role. Highlight your experience in machine learning, especially in life sciences and bioinformatics. We want to see how your skills align with our mission of revolutionising drug discovery!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about the role and how you can contribute to our team. We love seeing enthusiasm for both machine learning and the biotech field, so let that passion come through!
Showcase Your Projects: If you've worked on relevant projects, make sure to showcase them! Whether it's building ML systems or collaborating with biologists, we want to see examples of your work. This helps us understand your hands-on experience and problem-solving skills.
Apply Through Our Website: We encourage you to apply directly through our website. It streamlines the process and ensures your application gets to the right people. Plus, it shows us you're serious about joining our elite team in Oxford!
How to prepare for a job interview at SR2 | Socially Responsible Recruitment | Certified B CorporationTM
✨Know Your Bio-ML Stuff
Make sure you brush up on your machine learning fundamentals, especially as they relate to bioinformatics and computational biology. Be ready to discuss specific projects where you've applied ML techniques to biological datasets, and how you tackled challenges in those areas.
✨Showcase Your End-to-End Experience
Since this role involves owning the entire ML lifecycle, prepare examples that highlight your experience from data collection to model deployment. Talk about the tools you've used, like Python and PyTorch or TensorFlow, and how you've built production-ready systems rather than just prototypes.
✨Collaborate Like a Pro
This position requires close collaboration with biologists, so be prepared to discuss how you've worked with cross-functional teams in the past. Share examples of how you translated complex experimental problems into actionable ML solutions, and how you communicated technical concepts to non-technical team members.
✨Emphasise Your Leadership Skills
As a Lead Bio-ML Engineer, you'll be mentoring a small team. Highlight any previous leadership experiences, whether formal or informal, and discuss how you've helped others grow in their roles. Show that you're not just a tech whiz but also someone who can inspire and guide a team.