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Machine Learning Engineer - London

London, England, United Kingdom

About Valence Labs

Valence Labs is an AI research and productization engine within Recursion dedicated to industrializing scientific discovery to radically improve lives. Combining the intellectual freedom of academia with the resources and stability of industry, our focus is the development of highly-autonomous systems that will spearhead a fundamental shift in the way treatments are discovered and developed for complex disease. Our research is driven by optimism, purpose, and a shared vision for a healthier tomorrow. We publish in top journals and conferences, are deeply committed to open-science and open-source, and maintain some of the largest and most active research communities in our industry. Our team is located in London and Montreal, where we share close connections with Mila, the world’s largest deep learning research institute.

About the role

We’re seeking an experienced Machine Learning Researcher to shape and lead the development of software and AI systems that will help in our mission of industrializing scientific discovery to radically improve lives. We're looking for individuals with strong engineering skills, including expertise in designing, implementing, improving, and deploying machine learning systems. In addition, we highly value proficiency with state-of-the-art machine learning algorithms and exceptional problem solving skills. In this role, you will:

  • Develop and implement generative models (e.g., diffusion models, flow matching, score-based models).
  • Collaborate with researchers to push forward projects involving molecule, protein, and 3D structure generation.
  • Stay abreast of the latest advancements in generative AI and apply them to our structural data.
  • Collaborate with an interdisciplinary team of dry and wet lab scientists to inform and improve our models and systems.
  • Engage with and contribute to open-source libraries developed by Valence and the research community.
  • Present and communicate research findings through talks, blog posts, publications, and conferences.

A successful candidate will have most of the following:

  • PhD or Master's degree with industry experience.
  • Demonstrated expertise in generative models and experience applying these to structural biology or material science.
  • Proficiency in handling structural biology data and understanding of biochemical principles.
  • Strong programming skills and understanding of modern software development practices, especially in Python.
  • Experience in building and deploying high-performance implementations of deep learning algorithms.
  • Proven track record in machine learning, including designing new architectures, hands-on experimentation, analysis, visualization, and model deployment.
  • Demonstrated capability to understand and summarize scientific content and implement deep learning models based on descriptions from publications.
  • Passion for applying ML research to impactful problems.

Nice to have:

  • Authorship of publications in peer-reviewed conferences (e.g., NeurIPS, ICML, ICLR, or similar).
  • Contribution to high-visibility ML codebases.
  • Scientific knowledge of biology, chemistry, or physics along with previous experience working in a scientific environment across disciplines.

Valence Labs is committed to creating a diverse and inclusive environment, where understanding and accommodating personal needs and preferences is a priority. Join our multidisciplinary team of passionate researchers, eager to push the boundaries of ML research and contribute to industrializing scientific discovery to radically improve lives.

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Equal Opportunity Employment Information (Recursion)

Recursion is a proud equal opportunity employer. 

We have a fundamental belief that we can only achieve our mission if we truly commit to diversity, equity and inclusion. We believe diversity makes us stronger, and it's our responsibility to build an equitable and inclusive workplace where our diverse talent thrives.  To this end, we invite you to self-identify your race/ethnicity and gender. This information will be kept confidential and will not be shared with the hiring managers or otherwise considered as part of your application. Submission of this information is voluntary and refusal to provide any or all of the information requested will not subject you to any adverse treatment.  If you are willing, please let us know if you identify as belonging to any of the following groups:

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