Machine Learning Research Scientist

Valence Labs•Montreal, QC

8h•Hybrid

About The Position

We are seeking a Research Scientist with a hybrid research-engineering mindset to join our team. In this role, you will be at the forefront of developing generative architectures and foundation models that ground machine learning in real-world biological discovery.

Requirements

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.
Impactful research track record, including designing new neural networks to model molecular or biological systems, proposing new theories, or applying novel ML techniques to real-world problems.
Strong technical and engineering skills, including the ability to rapidly prototype ML models (Python proficiency required; Rust preferred for high performance molecular encoding or data pipelines).
Leadership and communication skills, including a lead authorship record in peer-reviewed conferences (e.g., NeurIPS, ICML, ICLR) or journals (e.g., Nature, Science, JACS).
Interdisciplinary empathy, with a proven ability to work effectively with interdisciplinary teams of dry and wet scientists.

Responsibilities

Research and develop state-of-the-art architectures (e.g., flow matching, diffusion models, geometric deep learning) tailored to specific biological or chemical challenges.
Build and maintain ML systems capable of processing massive datasets on high-performance compute clusters (BioHive).
Ensure ML predictions are biologically trustworthy and actionable by collaborating closely with drug discovery teams.
Publish findings in top-tier venues and contribute to the broader scientific community.