Machine Learning Engineer

Valence Labs is a research and productization engine within Recursion dedicated to advancing the frontier of AI in drug discovery. Combining the intellectual freedom of academia with the resources and stability of industry, we develop novel AI technologies to spearhead a fundamental shift in the way we discover and develop treatments 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 headquartered in Montreal, where we share close connections with Mila, the world’s largest deep learning research institute.

We’re seeking an experienced Research Engineer to shape and lead the development of software and AI systems that will help in our mission of decoding biology to radically improve lives. We're looking for individuals with strong engineering skills, including expertise in designing, implementing, improving, and deploying distributed machine learning systems at significant scale. In addition, we highly value proficiency with state-of-the-art machine learning algorithms and exceptional problem solving skills.

In this role, you will:

• Support Valence Labs’ research agenda across ML for drug discovery.
• Engage with and contribute to open-source libraries developed by Valence and the research community.
• Create and improve novel ML methods that will accelerate drug discovery.
• Collaborate with an interdisciplinary team of dry and wet lab scientists to inform and improve our models and systems.
• Effectively present and communicate research findings through talks, blog posts, publications, and conferences.

• PhD or equivalent practical experience in a technical field.
• Strong programming skills and understanding of modern software development practices, especially in Python.
• 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.
• Strong knowledge of linear algebra, calculus, and statistics.
• 4+ years of experience using ML and scientific computing frameworks.
• Passion for applying ML research to real-world problems.

• Experience in building and deploying high-performance implementations of deep learning algorithms.
• 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.

At Valence Labs, we foster an inclusive and diverse work environment. Join our multidisciplinary team of passionate researchers, eager to push the boundaries of ML research and contribute to technology that will transform drug discovery and human health.