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- Tasks: Lead innovative ML solutions for drug discovery while ensuring data privacy and security.
- Company: Mission-driven tech company in life sciences, focused on collaborative model development.
- Benefits: Up to £160,000 salary, attractive stock options, fully remote work, and flexible hours.
- Why this job: Make a real impact in drug discovery with cutting-edge technology and research.
- Qualifications: Hands-on experience in ML, deep knowledge of privacy risks, and strong publication record.
- Other info: Join a dynamic team with significant influence over technical direction and career growth.
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 will 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.
3 Month Plan:
- Develop a working understanding of the product, federated training setup, and key life-sciences modelling use cases.
- Reproduce and extend at least one existing modelling pipeline to establish a baseline privacy and attack-surface assessment.
- Contribute to privacy analysis for one or more active federated drug discovery programs as they transition from setup into live operation.
Experience needed:
- Hands-on experience with co-folding and structure-based models.
- Deep knowledge of federated learning and the nuances of privacy risk in distributed environments.
- You build experiments to prove (or disprove) privacy claims using quantitative and qualitative data.
- You own the 'messy' problems and can explain the why behind technical risks to non-technical leaders.
- A strong publication record in ML or Computational Biology.
- Experience working within industry consortia or complex partnerships.
- Past success influencing industry standards or regulatory privacy positions.
Remuneration:
- Fully Remote Working Culture
- Up to £160,000 Base Salary
- Attractive Stock Options
- B2B & Full time employee options
- Flexible hours + - 3 hours of CET time zone
If you think you are a good match for the role, send us your CV and if we think you are a good match, we will give you a call!
Principal Machine Learning Researcher (Privacy/Risk) | | Series A - Drug discovery Platform | Fully Remote, EU/UK | Base Salary Up to £160,000K, plus early equity+benefits in Bolton employer: Owen Thomas | Pending B Corp™
Contact Detail:
Owen Thomas | Pending 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 Up to £160,000K, plus early equity+benefits in Bolton
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those who work at companies you're interested in. A friendly chat can sometimes lead to job opportunities that aren't even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects and research. This is a great way to demonstrate your expertise in machine learning and privacy risk, making you stand out to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions and case studies related to ML and data privacy. Practising with a friend or using mock interview platforms can help you feel more confident when it’s your turn to shine.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, applying directly can sometimes give you an edge over other candidates.
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 Up to £160,000K, plus early equity+benefits in Bolton
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Principal Machine Learning Researcher. Highlight your hands-on experience with ADMET or structural biology modelling, and don’t forget to showcase your knowledge in federated learning and privacy risk!
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 skills align with our mission. Be specific about your experience with ML architecture and data privacy.
Showcase Your Publications: If you have a strong publication record, make sure to include it! This is a great way to demonstrate your expertise in ML or computational biology. Link to your work if possible, so we can see your contributions in action.
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 important updates from us!
How to prepare for a job interview at Owen Thomas | Pending B Corp™
✨Know Your Stuff
Make sure you have a solid grasp of machine learning concepts, especially around ADMET and federated learning. Brush up on the latest techniques like graph neural networks and transformers, as these will likely come up in conversation.
✨Showcase Your Experience
Prepare to discuss your hands-on experience with structure-based models and privacy risk management. Be ready to share specific examples of how you've tackled complex problems and influenced industry standards in your previous roles.
✨Understand the Company’s Mission
Familiarise yourself with the company’s focus on drug discovery and data privacy. Being able to articulate how your skills align with their mission will show that you're genuinely interested and invested in their work.
✨Ask Insightful Questions
Prepare thoughtful questions about their current projects, especially around privacy attack-surface assessments and model development. This not only shows your interest but also helps you gauge if the role is the right fit for you.