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Senior Machine Learning Scientist
Type: Full-time
Location: Remote (UK time ± 2 hours; UK preferred)
Compensation: Competitive salary
About us
- Bindbridge is advancing sustainable agriculture through AI-powered molecular glue discovery and design.
- Backed by Speedinvest and Nucleus Capital, we are building a computational platform to bring targeted protein degradation to agriculture.
- Our first goal is to discover herbicides that revolutionise crop protection while minimising environmental impact.
The role
- As a Senior Machine Learning (ML) Scientist you will build the next generation of our molecular glue discovery and design platform.
- You will set technical direction and own the quality bar day to day: review code and methods, decide what gets built and what gets cut, and scale research ideas from prototype to production.
- You will build the models that power the platform, from structure prediction through candidate design to the scoring layer that ranks them.
- You will own evaluation, building benchmarks that are honest about leakage, memorisation and held-out difficulty.
- You will translate the biology and chemistry team's research into concrete modelling strategies.
- You will help hire, onboard and mentor engineers as the team grows.
- This role is for a mission-driven technical leader who wants to push the frontier of AI for molecular design and turn that progress into crop protection that works.
What you will bring
- Significant experience applying ML to real-world problems in structural biology, chemistry or drug discovery.
- Proven experience leading ML teams and setting technical direction in a fast-paced, multi-disciplinary environment.
- Depth in at least one of: protein structure and complex prediction, docking or generative molecular design.
- Strong hands-on experience with PyTorch and the scientific Python ecosystem.
- Experience contributing to and maintaining deep-learning codebases, with a high bar for engineering quality, reproducibility and testing.
- The judgement to review methods, models and code you did not write, and to tell when a number is measuring the wrong thing.
- A collaborative approach to solving problems.
Nice to have
- Publications or open-source contributions in ML for structural biology, computational chemistry or drug discovery.
- PhD in a quantitative or computational field.
- Experience with targeted protein degradation, molecular glues, PROTACs or ternary complex modelling.
- Experience working in an interdisciplinary scientific environment, especially across ML, biology, chemistry and physics.
- Familiarity with the tools, data formats and workflows commonly used in computational biology and chemistry.
Why join us
- A chance to build the models behind the first AI-designed herbicides, in a field where targeted protein degradation has barely been applied.
- Significant ownership and independence as the senior technical seat on the platform.
- Competitive salary.
- A small, fast-moving team where what you build is what the company runs on.
Application process
- CV review - We look at what you have built and the depth of your ML and scientific experience.
- Introductory chat - An informal conversation about your experience and what you are looking for.
- Technical interview - A collaborative session working through a real problem from our platform together.
- Final interview - A conversation with the CEO about our mission and values.
- References and offer - We check references before making an offer if both sides wish to proceed.
What to expect
- Bindbridge is an equal opportunity employer. We welcome applicants of all backgrounds, and we encourage you to apply even if you do not match every line above.
- No advance preparation, take-home exercises or algorithmic coding tests at any stage.
- We do not use AI tools to assess candidates. Every application is reviewed by a person, and all hiring decisions are made by people.
- If any adjustments would help you take part, let us know when we contact you and we will be happy to discuss them.