At a Glance
- Tasks: Lead a high-performing team in developing AI models for drug discovery.
- Company: AI-native biotech startup transforming medicine discovery with cutting-edge technology.
- Benefits: Competitive salary, significant equity, and a collaborative culture focused on innovation.
- Other info: Join a dynamic team with excellent growth opportunities in a rapidly expanding field.
- Why this job: Make a real impact on human health through frontier AI and scientific research.
- Qualifications: Proven leadership in ML engineering, deep learning expertise, and strong communication skills.
The predicted salary is between 145000 - 145000 £ per year.
We’re an AI-native biotech company building foundation models for biology to transform how new medicines are discovered. By combining large-scale multimodal biological datasets with probabilistic machine learning and generative AI, we’re developing systems capable of predicting complex biological behaviour at unprecedented scale. Our mission is to create general-purpose biological intelligence that accelerates therapeutic discovery across oncology, immunology, and rare diseases.
We’re looking for a Machine Learning Team Lead to lead a high-performing team working on foundation models and probabilistic ML systems for drug discovery. You’ll sit at the intersection of research and engineering - driving technical direction, mentoring senior engineers and researchers, and helping scale both our platform and team as we push toward state-of-the-art biological modelling. This is a hands-on leadership role for someone excited by frontier AI, scientific impact, and building exceptional ML organisations.
- Leading a team of ML engineers and applied researchers building large-scale foundation models for biological data
- Defining technical strategy across probabilistic modelling, representation learning, and generative AI systems
- Architecting scalable distributed training infrastructure for multi-billion parameter models
- Collaborating with computational biologists, cheminformaticians, and leadership on long-term research initiatives
- Mentoring and growing a world-class ML engineering team
- Helping shape hiring strategy and technical roadmap as the company scales
Proven experience leading ML engineering or applied research teams. Strong background building and scaling deep learning systems in production. Deep understanding of foundation model architectures and modern generative AI techniques. Experience with probabilistic ML approaches such as Bayesian inference, latent variable models, or uncertainty-aware systems. Strong software engineering and distributed systems experience. Excellent communication and stakeholder management skills. Experience in biotech, computational biology, or AI for science. Publications or contributions in advanced ML research. Experience scaling ML organisations in startup environments.
Lead one of the most technically ambitious AI teams in biotech. Work on frontier AI problems with direct impact on human health. Competitive compensation and meaningful equity package. Collaborative culture built around scientific curiosity and engineering excellence.
Senior/Lead Machine Learning Engineer in London employer: SR2 | Socially Responsible Recruitment | Certified B Corporation™
As a leading AI-native biotech company based in London, we offer an exceptional work environment that fosters scientific curiosity and engineering excellence. Our collaborative culture encourages innovation and provides significant opportunities for professional growth, particularly for those passionate about frontier AI and its impact on human health. With competitive compensation and a meaningful equity package, we are committed to building a world-class team dedicated to transforming drug discovery through advanced machine learning.
Contact Details:
SR2 | Socially Responsible Recruitment | Certified B Corporation™ Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Senior/Lead Machine Learning Engineer in London
✨Tip Number 1
Network like a pro! Reach out to people in the biotech and AI space, especially those who work at companies you're interested in. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! If you’ve got projects or research that highlight your expertise in machine learning or AI, make sure to showcase them. A portfolio can speak volumes about your capabilities.
✨Tip Number 3
Prepare for interviews by diving deep into the company’s mission and recent projects. Tailor your responses to show how your experience aligns with their goals, especially in drug discovery and AI.
✨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, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior/Lead Machine Learning Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the role of a Senior/Lead Machine Learning Engineer. Highlight your leadership experience, technical expertise in ML, and any relevant projects in biotech or AI.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about AI in drug discovery. Share specific examples of how you've led teams or projects that relate to foundation models and probabilistic AI, and show us your enthusiasm for our mission.
Showcase Your Technical Skills:In your application, don’t shy away from detailing your technical skills. Mention your experience with deep learning systems, distributed training infrastructure, and any publications or contributions to advanced ML research that demonstrate your expertise.
Apply Through Our Website:We encourage you to apply directly through our website. This way, your application will be reviewed by our team, and you'll have a better chance of standing out in the process. Plus, it’s super easy!
How to prepare for a job interview at SR2 | Socially Responsible Recruitment | Certified B Corporation™
✨Know Your Stuff
Make sure you brush up on the latest in foundation models and probabilistic AI. Be ready to discuss your experience with deep learning systems and how you've applied them in production. This role is all about technical depth, so show them you’re not just familiar but passionate about these topics.
✨Showcase Leadership Skills
Since this is a team lead position, be prepared to talk about your leadership style. Share specific examples of how you've mentored engineers or researchers in the past. Highlight your experience in shaping technical strategies and how you’ve successfully scaled teams in a startup environment.
✨Collaborate Like a Pro
This role involves working closely with computational biologists and other stakeholders. Think of examples where you’ve collaborated across disciplines. Emphasise your communication skills and how you’ve managed stakeholder expectations in previous projects.
✨Be Ready for Technical Challenges
Expect some technical questions or case studies during the interview. Prepare to discuss how you would architect scalable distributed training infrastructure for large models. Practise explaining complex concepts in a way that’s easy to understand, as this will demonstrate your ability to communicate effectively with both technical and non-technical team members.
