At a Glance
- 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.
- Other info: Join a dynamic team with significant influence over technical direction and career growth.
- 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.
The predicted salary is between 160000 - 160000 £ per year.
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.
- 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.
- 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.
- 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 Leeds employer: Owen Thomas | B CorpTM
Join a mission-driven technology company at the forefront of drug discovery, where you'll have the opportunity to lead innovative machine learning initiatives in a fully remote environment. With a strong focus on employee growth, flexible working hours, and competitive compensation including early equity, this organisation fosters a collaborative culture that values your expertise while prioritising data privacy and security. Be part of a team that not only drives scientific advancements but also supports your professional development in a dynamic and impactful field.
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 Leeds
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those already working at companies you're interested in. A friendly chat can open doors and give you insider info that could help you stand out.
✨Tip Number 2
Show off your skills! If you've got projects or research that highlight your expertise in machine learning or data privacy, make sure to share them. A portfolio or GitHub can really set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by diving deep into the company's mission and values. Tailor your responses to show how your experience aligns with their goals, especially in drug discovery and data security.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love hearing from passionate candidates who are ready to make an impact in the life sciences domain.
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 Leeds
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 data privacy.
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 privacy risk.
Showcase Your Publications:If you've got 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.
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!
How to prepare for a job interview at Owen Thomas | B CorpTM
✨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 privacy risk in distributed environments. Be ready to share specific examples of how you've tackled 'messy' problems and influenced industry standards or regulatory positions.
✨Understand the Company’s Mission
Familiarise yourself with the company’s mission in the life sciences domain. Knowing how your role as a Principal Machine Learning Researcher fits into their drug discovery platform will show your genuine interest and alignment with their goals.
✨Prepare Questions
Have insightful questions ready about their federated data infrastructure and how they approach data privacy. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you.
