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- Tasks: Design cutting-edge algorithms and develop advanced models for real-world AI challenges.
- Company: High-growth AI-native drug design startup in Central London.
- Benefits: Up to £130,000 salary, private medical insurance, and hybrid working.
- Other info: Enjoy a supportive culture with social events and excellent career growth.
- Why this job: Join a team making a real impact in oncology and global health.
- Qualifications: PhD or significant experience in Molecular AI and strong engineering skills.
The predicted salary is between 130000 - 130000 £ per year.
I am currently partnering with a high-growth, AI-native drug design startup based in Central London that is fundamentally changing how chemistry teams progress their programs. While many in the space struggle with fragmented data, this team has built a proprietary platform using curated, non-public experimental data — aggregated from patents and global partners — to predict molecule properties with unprecedented accuracy. Since their launch in 2023, their technology has already been adopted by hundreds of chemists worldwide, impacting real-world programs in oncology, dementia, and global health.
As an ML Engineer, you won’t just be a cog in a machine; you will be a foundational member of the team, designing cutting-edge algorithms to solve the industry’s most complex "real-world" AI challenges.
- Innovate: Develop advanced models to predict ligand-target interactions.
- Build: Create production-quality software, integrating structure-based algorithms into a global platform.
- Collaborate: Work at the intersection of physics, chemistry, biology, and ML to translate scientific needs into product reality.
- Own: You will have the freedom to drive innovation and shape the company’s technological framework from its inception.
This team values outcomes over outputs and looks for individuals who thrive on autonomy and proactive problem-solving.
- Deep Expertise: You hold a PhD, Postdoc, or significant industry experience in Molecular AI.
- Engineering Rigor: Strong skills in scientific computing, deep learning frameworks, and modern version control. Strong experience with either Alphafold, Boltz or Chai.
- Cloud Fluency: Comfort working with AWS, GCP, or Azure (Infrastructure-as-code).
- Interdisciplinary: You can communicate complex technical concepts to both scientists and stakeholders.
- Bonus Points: Any experience with structure prediction, open-source contributions (like RDKit or PyTorch), or deploying models to production is a major plus.
Location: Based in a beautiful, historic office in Victoria House, London.
Flexibility: Hybrid working.
Equity: A highly competitive option plan.
Culture: A high-performing, supportive environment with frequent social events and off-sites.
Benefits: Private medical insurance, Cycle to Work scheme, and a strong pension (5%/5%).
If you are interested in this role, drop over your CV and if we think you are a good match we will give you a call!
Machine Learning Engineer, Alphafold, Boltz, Chai, Drug Discovery | B2B AI Start-up | 3 Days PW in London | Up to £130,000 Plus Benefits employer: Owen Thomas | B Corp™
Contact Detail:
Owen Thomas | B Corp™ Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer, Alphafold, Boltz, Chai, Drug Discovery | B2B AI Start-up | 3 Days PW in London | Up to £130,000 Plus Benefits
✨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 refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to machine learning and drug discovery. 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 problem-solving skills. Practice coding challenges and be ready to discuss your past projects in detail. Confidence is key!
✨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 Machine Learning Engineer, Alphafold, Boltz, Chai, Drug Discovery | B2B AI Start-up | 3 Days PW in London | Up to £130,000 Plus Benefits
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Alphafold, Boltz, or Chai. 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 shine! Use it to explain why you’re excited about this opportunity and how you can contribute to our mission in drug discovery. Keep it engaging and personal!
Showcase Your Technical Skills: We’re looking for deep expertise in Molecular AI and strong engineering skills. Be sure to mention your experience with scientific computing, deep learning frameworks, and any cloud platforms you’ve worked with. Let us know what makes you stand out!
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 don’t miss out on any important updates from our team!
How to prepare for a job interview at Owen Thomas | B Corp™
✨Know Your Algorithms
Make sure you brush up on the algorithms relevant to the role, especially those related to Alphafold, Boltz, and Chai. Be prepared to discuss how you've applied these in real-world scenarios, as this will show your deep expertise and understanding of molecular AI.
✨Showcase Your Projects
Bring examples of your previous work, particularly any projects involving drug discovery or structure prediction. Highlight your contributions and the impact they had, as this will demonstrate your engineering rigor and ability to drive innovation.
✨Communicate Clearly
Practice explaining complex technical concepts in simple terms. Since you'll be working with both scientists and stakeholders, being able to bridge that gap is crucial. Think of examples where you've successfully communicated intricate ideas to non-technical audiences.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's technology and future direction. This shows your genuine interest in the role and helps you assess if the company culture aligns with your values, especially regarding autonomy and proactive problem-solving.