Machine Learning Research Scientist

Recursion
London
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Scientist

Research Data Scientist Intern - Tesco

Research Data Scientist Intern - Tesco

Research Data Scientist Intern

Research Data Scientist Intern - Tesco

Research Data Scientist Intern

About Valence Labs

Valence Labs is Recursion’s frontier AI research engine. We lead high-impact research programs designed to materially expand Recursion’s ability to discover and develop medicines for complex diseases. Our team balances near-term pragmatism with a long-term view of where the field is heading in the next 3–5 years, incubating, designing, and productizing the approaches we believe will define the future of drug discovery.

Our work is driven by optimism, purpose, and a shared vision for a healthier tomorrow. We publish in top journals and conferences, contribute to open science, and engage with some of the world’s most active ML-for-drug-discovery research communities. Our teams are based in London and Montreal, with deep ties to Mila, the world’s largest deep-learning research institute.

About The Role

We’re seeking an experienced ML Research Scientist to drive bold, ambitious research agendas across Valence Labs’ primary research programs, including multi-omic foundation models, next-generation structural biology and atomistic modeling, and approaches for autonomous science. We’re looking for individuals who can articulate and execute a research vision, lead long-running technical projects, and work fluidly across disciplines. You’ll combine mastery of modern machine learning with strong scientific intuition and exceptional engineering skills to develop AI systems that meaningfully accelerate drug discovery. In this role, you will:

  • Lead and contribute to frontier research programs in ML for drug discovery, including generative models, multi-omic representation learning, and atomistic/structural modeling.
  • Own a research agenda end-to-end: ideation, implementation, experimentation, evaluation, and deployment in collaboration with Recursion’s platform teams.
  • Collaborate closely with interdisciplinary teams of ML researchers, software engineers, wet-lab scientists, and domain experts to identify high-value research opportunities.
  • Communicate findings internally and externally through talks, publications, blog posts, and conference presentations.
  • Contribute to the broader scientific community through open-source, open-science, and collaboration initiatives.


Location: This position is based in Montreal, Canada or London, UK

A successful candidate will have most of the following:

  • PhD (or equivalent) with significant academic or industry research experience in a related technical field involving machine learning applied to drug discovery.
  • Scientific knowledge of biology, chemistry, or physics, along with previous experience working in a scientific environment across disciplines.
  • A proven track record of impactful machine learning research, including designing new neural networks to model molecular systems, proposing new theories, improving upon existing ideas, and applying novel ML techniques to real-world problems.
  • Strong technical and engineering skills, including ability to rapidly prototype ML models.
  • Comfort working cross-functionally with interdisciplinary teams of dry and wet scientists.
  • Experience in project supervision, leadership, or management, including lead authorship in publications at peer-reviewed conferences (e.g., NeurIPS, ICML, or ICLR) and/or journals (e.g. Nature, Science, JACS, or ACS).


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.

Working Location & Compensation:

This is an office-based, hybrid position at one of our offices located in Montreal, Quebec, or London, England. Employees are expected to work in the office at least 50% of the time.

At Recursion, we believe that every employee should be compensated fairly. Based on the skill and level of experience required for this role, the estimated current annual base range for this role is £103,000 to £118,000 (GBP). You will also be eligible for an annual bonus and equity compensation, as well as a comprehensive benefits package.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.