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-performing team and make a real impact in healthcare.
- Qualifications: Experience in ML systems, ADMET data, and strong software engineering skills.
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 employer: Owen Thomas | B Corp™
Join a pioneering AI-native drug design scale-up in the heart of Central London, where you will play a crucial role in revolutionising pharmaceutical research. With a strong emphasis on employee ownership and accountability, the company fosters a collaborative culture that prioritises continuous learning and innovation. Enjoy competitive equity options, modern benefits including private medical insurance, and the flexibility of remote working, all while being part of a high-performing team dedicated to impactful drug discovery.
StudySmarter Expert Advice🤫
We think this is how you could land ML Engineer, Drug Discovery (ADMET) – Production‑Ready AI
✨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
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 engage with us directly.
We think you need these skills to ace ML Engineer, Drug Discovery (ADMET) – Production‑Ready AI
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with ML systems and ADMET data. We want to see how your skills align with our needs, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Tell us why you’re excited about the role and how you can contribute to our mission. Keep it concise but impactful—show us your passion for drug discovery and AI.
Showcase Your Technical Skills:We’re looking for engineering excellence, so make sure to mention your hands-on experience with MLOps tooling and cloud platforms like AWS or GCP. Highlight any specific projects where you’ve built production-grade systems.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any updates from our team. Let’s get started on this journey together!
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 built and deployed ML systems, focusing on the engineering excellence that sets you apart.
✨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, as this will demonstrate your ability to work closely with chemistry teams.
✨Emphasise Ownership and Impact
This company values accountability, so be prepared to share examples of how you've taken ownership of projects and driven impactful results. Show them that you thrive in environments where you're responsible for your contributions.
