Machine Learning Scientist

Metric Bio; Vancouver; On-site; CAD 100,000 - 140,000; Full time

Job summary

Metric Bio is seeking a Machine Learning Scientist to accelerate small molecule drug discovery. The role involves designing advanced ML architectures and collaborating with experts in a fast-paced environment, impacting human health through groundbreaking research.

Benefits

Work on innovative applications of AI

Join a lean team valuing curiosity and autonomy

Impactful drug discovery projects

Qualifications

• Strong publication record in top ML conferences.
• 2+ years of experience writing production-quality research code.
• Deep understanding of uncertainty modeling and Bayesian optimization.

Responsibilities

• Design and implement novel machine learning architectures.
• Collaborate with interdisciplinary experts across chemistry and pharmacology.
• Publish in top-tier ML venues and contribute to the scientific roadmap.

Skills

Machine Learning

Deep Learning

Generative Modeling

Computational Chemistry

Python

Education

Ph.D. in Computer Science, Applied Mathematics, or related field

Tools

PyTorch

Job description

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Recruitment Partner | Biotech R&D | Computational Bio & Chem

Machine Learning Scientist – Drug Discovery (Small Molecules)

About the Opportunity

Small molecule drug discovery is one of the most high-impact and intellectually demanding challenges in modern machine learning. Traditional pharmaceutical development is costly, slow, and heavily reliant on trial-and-error, often taking over a decade and billions of dollars to bring a single new drug to market. This presents a massive opportunity for machine learning to transform the space by enhancing prediction accuracy, enabling generative molecular design, and drastically shortening development cycles.

This role offers the opportunity to work at the intersection of deep learning, generative modeling, and computational chemistry, with the goal of radically accelerating the discovery of novel therapeutics. You will be part of a team that has spent years pushing the boundaries of ML for drug development, collaborating with top-tier pharma clients, and publishing impactful research.

Your Impact

As a Machine Learning Scientist, you will :

• Design and implement novel machine learning architectures (e.g., diffusion models, graph neural networks, Transformers) tailored to the optimization of small molecule properties.
• Drive research-first development : test new algorithmic approaches, quantify uncertainty, and contribute to the creation of a robust and generalizable ML platform for molecular design.
• Collaborate with interdisciplinary experts across chemistry, pharmacology, and software engineering to bring research concepts into practical applications.
• Contribute to the scientific roadmap of an ML-native drug discovery platform, influencing both technical direction and applied use cases.
• Publish in top-tier ML venues (NeurIPS, ICML, ICLR), where appropriate, and participate in broader scientific dialogue.

What We’re Looking For

• Ph.D. in Computer Science, Applied Mathematics, Statistics, Physics, or a closely related quantitative discipline.
• Strong publication record , preferably as a first author, in top ML conferences (e.g., NeurIPS, ICML, ICLR).
• Deep understanding of modern machine learning, including :
• Transformers and attention mechanisms
• Uncertainty modeling and Bayesian optimization
• Fluency in Python and deep learning frameworks such as PyTorch .
• 2+ years of experience writing production-quality research code (version control, code review, unit testing, etc.).
• Demonstrated ability to work autonomously on open-ended research problems.

No prior experience in chemistry or biology is required — domain knowledge will be provided through close collaboration with internal experts.

Why This Role?

• Work on one of the most ambitious and meaningful applications of AI : using machine learning to solve real-world problems in drug development .
• Join a lean, elite team of researchers and scientists who value curiosity, autonomy, and technical depth.
• Rapid iteration cycle : datasets are small enough to train meaningful models in days, not months — enabling true research velocity .
• Contribute to real-world drug discovery projects that have the potential to impact human health at scale .

If you're passionate about applying your ML expertise to meaningful, cross-disciplinary challenges — and want to work at the frontier of science and technology — this is a rare and rewarding opportunity.

Seniority level

Seniority level

Mid-Senior level

Employment type

Employment type

Full-time

Job function

Job function

Science

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