At a Glance
- Tasks: Design cutting-edge algorithms to tackle real-world AI challenges in drug discovery.
- Company: High-growth AI-native drug design startup based in Central London.
- Benefits: Up to £130,000 salary, private medical insurance, and a Cycle to Work scheme.
- Other info: Enjoy hybrid working in a supportive environment with frequent social events.
- Why this job: Join a team making a real impact on global health with innovative technology.
- Qualifications: PhD or significant experience in Molecular AI and strong skills in scientific computing.
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.
- 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.
- 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. Comfort working with AWS, GCP, or Azure (Infrastructure-as-code).
- Bonus Points: Any experience with structure prediction, open-source contributions (like RDKit or PyTorch), or deploying models to production is a major plus.
Based in a beautiful, historic office in Victoria House, London. Hybrid working in 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 in City of London employer: Owen Thomas | B Corp™
Join a pioneering AI-native drug design startup in Central London, where you will play a crucial role in transforming the future of chemistry with cutting-edge technology. Enjoy a vibrant work culture that fosters collaboration and innovation, alongside excellent benefits such as private medical insurance and a strong pension scheme. With opportunities for professional growth and a supportive environment, this is an ideal place for passionate individuals looking to make a meaningful impact in drug discovery.
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 in City of London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals 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 potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common ML scenarios and be ready to discuss your past experiences 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 in City of London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your experience with molecular AI, deep learning frameworks, and any relevant projects that showcase your skills in scientific computing.
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 the company's mission. Be genuine and let your enthusiasm show!
Showcase Your Projects:If you've worked on any relevant projects, especially those involving structure prediction or deploying models, make sure to include them. This gives us a glimpse into your hands-on experience and problem-solving abilities.
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It streamlines the process and ensures your application lands directly in our 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 machine learning, especially those used in drug discovery. Be ready to discuss how you've applied these in your previous work or projects, as this will show your deep expertise and understanding of the field.
✨Showcase Your Collaboration Skills
Since the role involves working at the intersection of various scientific disciplines, prepare examples of how you've successfully collaborated with teams from different backgrounds. Highlight any experiences where you translated complex scientific needs into practical solutions.
✨Familiarise Yourself with Their Tech Stack
Get to know the tools and platforms mentioned in the job description, like AWS, GCP, or Azure. If you have experience with infrastructure-as-code, be ready to discuss it. This shows that you're not just a theoretical expert but also someone who can hit the ground running.
✨Prepare for Technical Questions
Expect technical questions that test your knowledge of scientific computing and deep learning frameworks. Practise coding challenges or algorithm problems that are relevant to the role. This will help you demonstrate your engineering rigor and problem-solving skills.
