At a Glance
- Tasks: Build advanced ML models and shape tech frameworks in drug discovery.
- Company: Innovative AI start-up revolutionising pharmaceutical research.
- Benefits: Competitive salary, equity options, private medical insurance, and flexible working.
- Other info: Dynamic culture with social events and opportunities for continuous learning.
- Why this job: Join a high-impact team and make a difference in healthcare with cutting-edge technology.
- Qualifications: Experience in ML systems, strong software engineering skills, and cloud fluency.
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.
This isn't just a research role; it’s about building robust, production‑grade systems at the intersection of biology, chemistry, and machine learning. You will be instrumental in shaping their technological framework from its inception.
- Model Development: Build advanced molecular property prediction models and expand their AutoML pipelines.
- Infrastructure & MLOps: Architect 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.
Who You Are
The team prioritizes outcomes over outputs and values "Ownership". They are looking for someone who thrives in an environment where they aren't dictated to, but are held accountable for their impact.
- Production Experience: You have demonstrable industry experience building and deploying ML systems in production, going beyond simple research prototypes. Experience working specifically with ADMET Data.
- Engineering Excellence: Strong software engineering skills and hands‑on experience with MLOps tooling, containerization, and model serving.
- Cloud Fluency: Highly comfortable with AWS, GCP, or Azure and Infrastructure‑as‑Code.
- Communication: Ability to collaborate across disciplines and present technical findings clearly.
Bonus Points: A PhD in Chemistry or Computer Science, experience with RDKit/PyTorch, or a track record of open‑source contributions.
Why Join?
- Equity: A competitive option plan aligned with the early stage of the company.
- Modern Benefits: Private medical insurance, a 5%/5% pension scheme, and the Cycle to Work scheme.
- Flexibility: 1‑week remote working allowed per quarter.
- Culture: Frequent social events and off‑sites with a team that values continuous learning and "Perseverance".
If you are interested, drop over your CV and if we think you are a good fit, we will give you a call!
ML Engineer, Drug Discovery (ADMET) – Production‑Ready AI in London employer: Owen Thomas | B Corp™
Join a pioneering AI-native drug design scale-up in the heart of Central London, where you will be part of a dynamic team dedicated to transforming pharmaceutical research. With a strong emphasis on employee ownership and accountability, the company offers competitive equity options, modern benefits including private medical insurance and a pension scheme, and a culture that fosters continuous learning through frequent social events and off-sites. This is an exceptional opportunity for a Machine Learning Engineer to make a significant impact in drug discovery while enjoying a flexible work environment.
StudySmarter Expert Advice🤫
We think this is how you could land ML Engineer, Drug Discovery (ADMET) – Production‑Ready AI in 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 ML systems and ADMET data. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on both technical and soft skills. Be ready to discuss your experience with MLOps tooling and how you've collaborated with cross-functional teams. Practice makes perfect!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love hearing from passionate candidates who are eager to join our innovative team.
We think you need these skills to ace ML Engineer, Drug Discovery (ADMET) – Production‑Ready AI in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of ML Engineer in Drug Discovery. Highlight your experience with ADMET data and any relevant projects that showcase your skills in building production-ready systems.
Showcase Your Impact:We want to see how you've made a difference in your previous roles. Use specific examples to demonstrate your ownership and accountability, especially in ML projects that have had real-world applications.
Keep It Clear and Concise:When writing your application, clarity is key! Avoid jargon overload and make sure your technical skills and experiences are easy to understand. We appreciate straightforward communication.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your CV and get you into our system quickly. We can’t wait to hear from you!
How to prepare for a job interview at Owen Thomas | B Corp™
✨Know Your Stuff
Make sure you brush up on your knowledge of ADMET data and its relevance in drug discovery. Be prepared to discuss how you've applied machine learning in production settings, especially in relation to molecular property prediction models.
✨Showcase Your Engineering Skills
Highlight your experience with MLOps tooling and cloud platforms like AWS, GCP, or Azure. Be ready to talk about specific projects where you’ve built robust ML systems and how you approached challenges in model serving and infrastructure.
✨Communicate Clearly
Since collaboration is key, practice explaining complex technical concepts in simple terms. Think about how you can translate scientific needs into actionable solutions and be ready to share examples of successful teamwork.
✨Emphasise Ownership and Impact
This company values accountability, so come prepared to discuss instances where you took ownership of a project. Share how your contributions made a tangible impact and how you thrive in environments that prioritise outcomes over outputs.
