At a Glance
- 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 a strong pension.
- Other info: Enjoy hybrid working, a supportive culture, and frequent social events.
- Why this job: Join a team revolutionising drug discovery with innovative technology and impactful projects.
- Qualifications: PhD or significant experience in Molecular AI and strong skills in deep learning.
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™
Join a pioneering AI-native drug design startup in Central London, where you will play a crucial role in shaping innovative solutions that impact global health. Enjoy a flexible hybrid working environment, competitive equity options, and a supportive culture that prioritises collaboration and personal growth, all while being part of a team that is transforming the future of chemistry. With excellent benefits including private medical insurance and a strong pension plan, this is an opportunity to make a meaningful impact in a high-growth sector.
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 expertise 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 take that extra step to connect with us directly.
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 reflects the skills and experiences that align with the Machine Learning Engineer role. Highlight your expertise in molecular AI, deep learning frameworks, and any relevant projects you've worked on.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about drug discovery and how your background makes you a perfect fit for our team. Be sure to mention any specific experience with Alphafold, Boltz, or Chai.
Showcase Your Projects:If you've worked on any interesting projects, especially those involving structure prediction or deploying models to production, make sure to include them. We love seeing real-world applications of your skills!
Apply Through Our Website:For the best chance of getting noticed, apply directly through our website. It helps us keep track of applications and ensures your CV lands in the right hands!
How to prepare for a job interview at Owen Thomas | B Corp™
✨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.
✨Communicate Clearly
Since you'll be working at the intersection of various disciplines, practice explaining complex technical concepts in simple terms. This will help you connect with both scientists and stakeholders during the interview, showcasing your interdisciplinary skills.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's technology and future direction. This not only shows your genuine interest in the role but also gives you a chance to assess if the company culture aligns with your values, especially regarding autonomy and innovation.
