At a Glance
- Tasks: Design cutting-edge algorithms to tackle real-world AI challenges in drug discovery.
- Company: High-growth AI-native startup revolutionising chemistry with innovative technology.
- Benefits: Up to £130,000 salary, private medical insurance, and a strong pension plan.
- Other info: Enjoy hybrid working, a supportive culture, and exciting social events.
- Why this job: Join a pioneering team making a real impact on global health and oncology.
- 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—demonstrate them! Share examples of complex problems you've solved in previous roles, especially those involving interdisciplinary collaboration. We love seeing how you tackle challenges head-on!
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s the quickest way for us to receive your application and start the conversation about how you can be part of our exciting journey in AI-driven drug design!
How to prepare for a job interview at Owen Thomas | B CorpTM
✨Know Your Algorithms
Make sure you brush up on the latest algorithms related to molecular AI, especially those used in Alphafold, Boltz, and Chai. Be ready to discuss how you've applied these in your previous work or research, as this will show your deep expertise and understanding of the field.
✨Showcase Your Projects
Prepare to talk about specific projects where you've developed advanced models or integrated structure-based algorithms. Highlight your role in these projects and the impact they had, as this demonstrates your ability to innovate and own your work.
✨Interdisciplinary Communication
Since the role requires collaboration across various fields, practice explaining complex technical concepts in simple terms. Think of examples where you've successfully communicated with both scientists and stakeholders, as this will showcase your ability to bridge gaps between disciplines.
✨Familiarise with Cloud Platforms
Get comfortable discussing your experience with cloud services like AWS, GCP, or Azure. Be prepared to share how you've used Infrastructure-as-code in your projects, as this is crucial for building production-quality software in a modern environment.
