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- Tasks: Build cutting-edge ML systems for drug discovery and collaborate with top chemists.
- Company: Innovative AI start-up revolutionising pharmaceutical research.
- Benefits: Up to £130,000 salary, private medical insurance, and flexible remote work options.
- Other info: Enjoy frequent social events and opportunities for continuous learning.
- Why this job: Join a high-performing team and make a real impact in healthcare innovation.
- Qualifications: Experience in ML systems, strong software engineering skills, and familiarity with ADMET data.
The predicted salary is between 130000 - 130000 £ per year.
I am currently representing an AI-native drug design scale-up that is solving the "sparse data" problem in pharmaceutical research. While most of the industry relies on public data, this company has built a proprietary platform fueled by curated, non-public experimental measurements — including potency, binding, and ADMET — aggregated from exclusive partners and patents.
Since their 2023 launch, their platform has been adopted by hundreds of chemists globally to accelerate drug programs in oncology, dementia, and inflammation. They are now looking for a seasoned ML Engineer to join their high-performing team in Victoria House, Central London, to help supercharge the next phase of their product.
The role involves building robust, production-grade systems at the intersection of biology, chemistry, and machine learning. Responsibilities include:
- Architecting the core ML infrastructure, including training pipelines, experiment tracking, model registries, and CI/CD for models.
- Data Curation: Curate and prepare specialized datasets of molecular properties.
- User-Centric Innovation: Work closely with chemistry teams and stakeholders to translate scientific needs into actionable technical solutions.
- Production Experience: Demonstrable industry experience building and deploying ML systems in production, going beyond simple research prototypes. Experience working specifically with ADMET.
- Engineering Excellence: Strong software engineering skills and hands-on experience with MLOps tooling, containerization, and model serving. Highly comfortable with AWS, GCP, or Azure and Infrastructure-as-Code.
Bonus Points: A PhD in Chemistry or Computer Science, experience with RDKit/PyTorch, or a track record of open-source contributions.
Modern Benefits: Private medical insurance, a 5%/5% pension scheme, and the Cycle to Work scheme.
Flexibility: 1-week remote working allowed per quarter. Frequent social events and off-sites with a team that values continuous learning and "Perseverance".
If you are interested, please drop over your CV and if we think you are a good fit, we will give you a call!
Machine Learning Engineer, ADMET, 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, ADMET, Drug Discovery | B2B AI Start-up | 3 Days PW in London | Up to £130,000 Plus Benefits
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, conferences, or even online webinars related to machine learning and drug discovery. You never know who might have a lead on that perfect job!
✨Show Off Your Skills
Create a portfolio showcasing your projects, especially those involving ADMET data or ML systems. Share it on platforms like GitHub or your personal website. This gives potential employers a taste of what you can do beyond just a CV.
✨Ace the Interview
Prepare for technical interviews by brushing up on your ML concepts and coding skills. Practice common interview questions and consider mock interviews with friends or mentors. Confidence is key, so show them you know your stuff!
✨Apply Through Us!
Don’t forget to apply through our website! We’re here to help you land that Machine Learning Engineer role. Plus, we know the ins and outs of the company and can give you tips to stand out in the process.
We think you need these skills to ace Machine Learning Engineer, ADMET, 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 role of Machine Learning Engineer. Highlight your experience with ADMET data and any relevant projects that showcase your skills in building production-grade ML systems.
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 at StudySmarter. Keep it concise but impactful!
Showcase Your Technical Skills: Don’t forget to mention your hands-on experience with MLOps tooling, containerization, and cloud platforms like AWS or GCP. We want to see how you can contribute to our core ML infrastructure!
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any updates from us!
How to prepare for a job interview at Owen Thomas | B Corp™
✨Know Your Stuff
Make sure you brush up on your machine learning fundamentals, especially as they relate to drug discovery and ADMET data. Be ready to discuss your past projects and how you've built and deployed ML systems in production.
✨Showcase Your Collaboration Skills
This role involves working closely with chemistry teams, so be prepared to talk about how you've translated scientific needs into technical solutions. Share examples of successful collaborations and how you’ve communicated complex ideas to non-technical stakeholders.
✨Demonstrate Your Engineering Excellence
Highlight your software engineering skills and experience with MLOps tooling. Be specific about the tools you've used, like AWS, GCP, or Azure, and any Infrastructure-as-Code practices you've implemented. This will show that you can build robust systems.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's platform and their approach to solving the sparse data problem. This shows your genuine interest in their work and helps you understand if the company is the right fit for you.