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 collaboration and innovation.
- Benefits: Up to £160,000 salary, attractive stock options, and fully remote work.
- Other info: Flexible hours and significant influence over technical direction in a dynamic environment.
- Why this job: Make a real impact in drug discovery with cutting-edge technology and research.
- Qualifications: Hands-on experience in ML, privacy risk, and strong publication record required.
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 Bolton 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. Here, you can make a meaningful impact in life sciences while enjoying the benefits of a supportive and dynamic workplace.
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 people 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 friends 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! 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 make an impact in drug discovery.
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 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 sure to mention any relevant publications or projects that demonstrate your expertise.
Showcase Your Technical Skills:In your application, be specific about the ML techniques you’ve used, like graph neural networks and transformers. We want to see how you’ve applied these in real-world scenarios, especially in relation to data security and privacy.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get all the updates directly from us. Plus, we love seeing candidates who take that extra step!
How to prepare for a job interview at Owen Thomas | B CorpTM
✨Know Your Stuff
Make sure you brush up on your knowledge of machine learning, especially in the context of ADMET and structural biology modelling. Be ready to discuss specific techniques like graph neural networks and transformers, as well as how they apply to drug discovery.
✨Showcase Your Privacy Expertise
Since this role focuses heavily on data privacy and risk, prepare to talk about your experience with federated learning and privacy attack-surface assessments. Have examples ready that demonstrate how you've tackled privacy challenges in past projects.
✨Collaborative Spirit
This position involves working closely with leadership and mentoring others. Think of instances where you've successfully collaborated or influenced technical direction in a team setting. Highlight your ability to communicate complex ideas to non-technical stakeholders.
✨Publication Power
A strong publication record is key for this role. Be prepared to discuss your research and any contributions to scientific publications or open-source software. This will show your commitment to advancing the field and your ability to contribute to the company's mission.
