Lead/Senior Machine Learning Engineer

Lead/Senior Machine Learning Engineer

Full-Time 145000 - 145000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Lead a high-performing team in developing AI models for drug discovery.
  • Company: AI-native biotech startup transforming medicine with cutting-edge technology.
  • Benefits: Competitive salary, significant equity, and a collaborative culture.
  • Other info: Join a dynamic team at the forefront of AI and biotech.
  • Why this job: Make a real impact on human health through innovative AI solutions.
  • Qualifications: Proven leadership in ML engineering and deep learning systems.

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.

Lead/Senior Machine Learning Engineer employer: SR2 | Socially Responsible Recruitment | Certified B Corporation™

As a pioneering 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, while our competitive compensation and meaningful equity package reflect our commitment to rewarding talent. Join us to lead a high-performing team at the forefront of drug discovery, where your contributions will have a direct impact on human health.

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Contact Details:

SR2 | Socially Responsible Recruitment | Certified B Corporation™ Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Lead/Senior Machine Learning Engineer

Tip Number 1

Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.

Tip Number 2

Show off your skills! Create a portfolio showcasing your projects, especially those related to foundation models and probabilistic AI. This will give you an edge and demonstrate your hands-on experience to potential employers.

Tip Number 3

Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts clearly, as communication is key in this role. We want to see how you can lead and mentor others!

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 mission to transform drug discovery.

We think you need these skills to ace Lead/Senior Machine Learning Engineer

Machine Learning
Probabilistic Modelling
Generative AI
Deep Learning
Foundation Model Architectures
Bayesian Inference
Latent Variable Models

Some tips for your application 🫡

Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the role of a Machine Learning Team Lead. Highlight your leadership experience, technical expertise in ML, and any relevant projects in biotech or AI that showcase your capabilities.

Craft a Compelling Cover Letter:Your cover letter is your chance to tell us why you're the perfect fit for our team. Share your passion for AI and drug discovery, and explain how your background in probabilistic ML and generative AI can contribute to our mission.

Showcase Your Projects:Include links to any relevant projects or publications that demonstrate your experience with foundation models and deep learning systems. This gives us a glimpse into your hands-on work and technical prowess.

Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity to lead our ML team in transforming drug discovery.

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 real-world scenarios, especially in biotech or similar fields.

Showcase Your Leadership Skills

Since this role involves leading a team, be prepared to share examples of how you've mentored others and driven technical direction. Highlight any experiences where you've successfully scaled ML teams or projects, as this will resonate well with the interviewers.

Communicate Clearly

Excellent communication is key! Practice explaining complex concepts in simple terms. You might need to collaborate with computational biologists or other non-technical stakeholders, so being able to bridge that gap is crucial.

Ask Insightful Questions

Prepare thoughtful questions about the company's mission and future projects. This shows your genuine interest in their work and helps you gauge if their goals align with your own aspirations in the field of AI and drug discovery.