Valence Labs
Machine Learning Research Scientist
Montréal, Quebec
Sponsorship not specifiedDetected 14 days ago
PythonMachine LearningDeep LearningData EngineeringResearchLeadershipCommunicationCollaboration
About the role
- We are seeking a Research Scientist with a hybrid research-engineering mindset to join our team.
- 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.
Responsibilities
- Scalable Engineering: Build and maintain ML systems capable of processing massive datasets on high-performance compute clusters (BioHive).
- Build and maintain ML systems capable of processing massive datasets on high-performance compute clusters (BioHive).
- We lead high-impact research
- programs designed to materially expand Recursion's ability to discover and develop medicines for complex diseases.
Requirements
- Compensation packages are competitive and commensurate with the skills and level of experience required for this role.
- Scientific knowledge of biology, chemistry, or physics, along with previous experience working in a scientific environment across disciplines.
- Interdisciplinary empathy, with a proven ability to work effectively with interdisciplinary teams of dry and wet scientists.
- packages are competitive and commensurate with the skills and level of experience required for this role.
Nice to have
- 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).
Compensation
- In addition to base salary you will also be eligible for an annual bonus and equity compensation, as well as a comprehensive benefits package.
- Compensation packages are competitive and commensurate with the skills and level of experience required for this role.
Benefits
- Our work is driven by optimism, purpose, and a shared vision for a healthier tomorrow.
- Our teams are based in London and Montreal, with deep ties to Mila, the world's largest deep-learning research institute.
- Model Innovation: Research and develop state-of-the-art architectures (e.g., flow matching, diffusion models, geometric deep learning) tailored to specific biological or chemical challenges.
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