At a Glance
- Tasks: Design cutting-edge algorithms to tackle real-world AI challenges in drug discovery.
- Company: High-growth AI-native startup revolutionising drug design in London.
- Benefits: Up to £130,000 salary, private medical insurance, and flexible hybrid working.
- Other info: Enjoy a supportive culture with social events and excellent career growth opportunities.
- Why this job: Join a pioneering team making a real impact on global health with innovative technology.
- Qualifications: PhD or significant experience in Molecular AI and strong programming 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 CorpTM
Join a pioneering AI-native drug design startup in Central London, where you'll be at the forefront of innovation in molecular AI. With a strong emphasis on flexibility and a supportive work culture, you will have the opportunity to drive impactful projects while enjoying competitive benefits, including private medical insurance and a robust pension plan. This is not just a job; it's a chance to shape the future of drug discovery alongside a talented team in a vibrant city.
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 is tailored to the Machine Learning Engineer role. Highlight your experience with Alphafold, Boltz, or Chai, and any relevant projects that showcase your skills in molecular AI. We want to see how you can contribute to our innovative team!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about drug discovery and how your background aligns with our mission. Be sure to mention specific technologies or methodologies you've worked with that relate to the role.
Showcase Your Problem-Solving Skills:In your application, don’t just list your skills—show us how you've used them to solve real-world problems. We love candidates who can demonstrate their proactive approach to tackling complex challenges in AI and chemistry.
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people. We can’t wait to hear from you!
How to prepare for a job interview at Owen Thomas | B CorpTM
✨Know Your Stuff
Make sure you brush up on your knowledge of Alphafold, Boltz, and Chai. Be ready to discuss how these tools can be applied in drug discovery and molecular AI. The more you know, the more confident you'll feel!
✨Showcase Your Projects
Prepare to talk about your previous work, especially any projects involving deep learning frameworks or cloud platforms like AWS, GCP, or Azure. Highlight specific challenges you faced and how you overcame them—this will show your problem-solving skills.
✨Communicate Clearly
Since this role involves working with both scientists and stakeholders, practice explaining complex technical concepts in simple terms. This will demonstrate your ability to bridge the gap between different disciplines, which is crucial for this position.
✨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 innovation.
