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- Tasks: Lead ML solutions for drug discovery, focusing on data privacy and innovative modelling techniques.
- Company: Mission-driven tech company in life sciences, fully remote opportunities across EU/UK.
- Benefits: Competitive salary up to £160,000, early equity, and comprehensive benefits.
- Other info: Collaborative environment with significant influence over technical direction and career growth.
- Why this job: Make a real impact in drug discovery while advancing your career in a cutting-edge field.
- Qualifications: Experience in machine learning, computational chemistry, and strong technical skills.
The predicted salary is between 160000 - 160000 £ per year.
The Client: A mission-driven technology company operating in the life sciences domain is seeking a Principal Scientist - hands-on with either ADMET or Structural Biology modelling, ML engineer to lead the technical direction for ADMET modeling efforts within its drug discovery platform. The organisation enables collaborative model development across partner organisations while maintaining strict data privacy and ownership, using a federated data infrastructure.
In this hands-on, high-impact role, you’ll work at the intersection of machine learning, computational chemistry, and applied research to advance foundational model applications in drug discovery. You'll be the technical authority on ML architecture, experimentation, and strategy, while focusing specifically on data security and privacy. You will also collaborate closely with leadership and mentor other engineers and researchers. While this is not a people management position, it offers significant influence over technical direction.
Responsibilities:- Lead the design and implementation of ML solutions for ADMET using cutting-edge techniques such as graph neural networks and transformers.
- Lead the research and implementation of data privacy within the models and establish privacy attack-surface assessment.
- Develop and extend models for specific applications, including data distillation, benchmarking, and evaluation.
- Define preprocessing and harmonization strategies for diverse assay datasets used in ADMET modeling.
- Author or contribute to scientific publications or open-source software where appropriate.
Principal Machine Learning Researcher (Privacy/Risk) | Series A - Drug discovery Platform | Fully Remote, EU/UK | Base Salary , plus early equity+benefits in Belfast employer: Owen Thomas | B Corp™
Contact Detail:
Owen Thomas | B Corp™ Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal Machine Learning Researcher (Privacy/Risk) | Series A - Drug discovery Platform | Fully Remote, EU/UK | Base Salary , plus early equity+benefits in Belfast
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at conferences. A personal connection can often get your foot in the door faster than a CV.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to ML and data privacy. This gives potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on technical questions and case studies relevant to drug discovery and ML. Practice makes perfect, so consider mock interviews with friends or mentors.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for passionate individuals who want to make an impact in the life sciences domain. Your dream job could be just a click away!
We think you need these skills to ace Principal Machine Learning Researcher (Privacy/Risk) | Series A - Drug discovery Platform | Fully Remote, EU/UK | Base Salary , plus early equity+benefits in Belfast
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Principal Machine Learning Researcher. Highlight your experience with ADMET, structural biology modelling, and any relevant machine learning techniques. We want to see how your skills align with our mission in drug discovery!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data privacy and how your background makes you a perfect fit for this role. Let us know what excites you about working at the intersection of machine learning and life sciences.
Showcase Your Projects: If you've worked on any projects related to ML architecture or data privacy, make sure to mention them! We love seeing practical examples of your work, especially if they relate to drug discovery or federated data infrastructure.
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’re considered for this exciting opportunity. Plus, it shows us you’re keen to join our team!
How to prepare for a job interview at Owen Thomas | B Corp™
✨Know Your Stuff
Make sure you brush up on the latest trends in machine learning, especially around ADMET and data privacy. Familiarise yourself with graph neural networks and transformers, as these are key to the role. Being able to discuss recent advancements or challenges in these areas will show your passion and expertise.
✨Showcase Your Hands-On Experience
Prepare to share specific examples of your previous work in ML architecture and experimentation. Highlight any projects where you’ve implemented privacy measures or worked with federated data infrastructures. This will demonstrate your practical skills and how they align with the company's mission.
✨Collaborative Spirit
Since this role involves working closely with leadership and mentoring others, be ready to discuss your approach to collaboration. Think of examples where you’ve successfully led a team or influenced technical direction without formal management authority. This will illustrate your ability to work well in a team-oriented environment.
✨Prepare Questions
Have a few thoughtful questions ready about the company’s approach to data security and privacy in ML models. This not only shows your interest in the role but also gives you insight into their values and practices. It’s a great way to engage with the interviewers and make a lasting impression.