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Senior Machine Learning Scientist | Python | Pytorch | Deep Learning | Generative Models | Chemistry | Hybrid, London

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United Kingdom
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Hybrid
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Senior Machine Learning Scientist | Python | Pytorch | Deep Learning | Generative Models | Chemistry | Hybrid, London


The opportunity

We're partnering with an ambitious, venture-backed deep-tech company pioneering a new frontier in AI-driven molecular discovery.


Operating at the intersection of machine learning, structural biology and computational chemistry, the company is developing a sophisticated AI platform designed to accelerate the discovery of novel molecules with significant real-world applications.


Its initial focus is transforming sustainable agriculture through the application of targeted protein degradation and molecular glues — bringing cutting-edge techniques from drug discovery into a largely unexplored scientific domain.


This is an opportunity to join a small, highly ambitious team and play a defining role in developing the technology underpinning the company's future.


The role

As a Senior Machine Learning Scientist, you'll take significant ownership of the company's core ML platform, helping shape both its scientific direction and technical architecture.

You'll work closely with specialists across machine learning, biology and chemistry, translating complex scientific challenges into innovative computational solutions.

Crucially, this isn't a role focused purely on experimentation or incremental model improvements. You'll have the autonomy to define technical strategy, establish best practices and take research from early-stage prototypes through to production.


Key responsibilities

  • Lead ML development: Drive the technical direction of the molecular discovery platform, making critical decisions around modelling approaches, architecture and research priorities.
  • Develop cutting-edge models: Build and optimise models spanning protein structure prediction, molecular docking, generative molecular design and candidate scoring.
  • Shape the research strategy: Collaborate with computational biologists and chemists to translate scientific discoveries into scalable ML solutions.
  • Establish technical excellence: Develop rigorous evaluation frameworks, robust benchmarks and reproducible ML pipelines.
  • Build for scale: Take promising research concepts from prototype to production, ensuring engineering quality and long-term maintainability.
  • Help grow the team: Contribute to hiring, mentoring and developing talented ML engineers and scientists.


What they're looking for

  • Significant experience applying machine learning to structural biology, computational chemistry or drug discovery.
  • Proven experience leading ML initiatives, setting technical direction and working in multidisciplinary research environments.
  • Deep expertise in at least one of protein structure prediction, protein complexes, molecular docking or generative molecular design.
  • Strong hands-on experience with PyTorch and the scientific Python ecosystem.
  • Experience developing and maintaining high-quality deep learning codebases.
  • Strong scientific judgement, particularly around model evaluation, reproducibility and experimental rigour.
  • A collaborative mindset and enthusiasm for solving complex scientific problems.


Desirable experience

  • PhD in a quantitative, computational or related scientific discipline.
  • Publications or open-source contributions in computational biology, chemistry or ML-driven molecular discovery.
  • Experience with targeted protein degradation, molecular glues, PROTACs or ternary complex modelling.
  • Experience working across ML, biology, chemistry and physics.


Why join?

  • Pioneer a new scientific frontier. Help develop AI technology in an area of molecular discovery that remains largely unexplored, with the potential to reshape sustainable agriculture.
  • Exceptional technical ownership. Take a senior technical position with genuine influence over the company's ML architecture, research direction and engineering standards.
  • Meaningful real-world impact. Work on complex scientific challenges with the potential to improve global crop protection while reducing environmental impact.
  • Early-stage opportunity with significant upside. Join a small, fast-moving, venture-backed team offering competitive compensation, meaningful equity and the opportunity to shape a company's technical foundations.
  • Research that becomes reality. Work in an environment where the models you develop directly power the company's core technology.


Interview process

The company operates a straightforward, collaborative interview process designed to assess practical experience and scientific thinking rather than performance on artificial coding exercises.


The process includes an initial conversation, a collaborative technical discussion, a final meeting with leadership and references.


No take-home assignments or algorithmic coding tests are required.


Senior Machine Learning Scientist | Python | Pytorch | Deep Learning | Generative Models | Chemistry | Hybrid, London

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