Senior Machine Learning Scientist

We’re looking for a Senior Machine Learning Scientist

VANCOUVER, BC (OR REMOTE) / 7+ YRS EXPERIENCE

Small molecule drug discovery is one of the most exciting open problems in machine learning. Significant advances would reduce ten years and two billion dollars currently required to develop a new drug, and save countless lives. The available datasets are large enough to benefit from sophisticated deep learning architectures, but small enough that models can be trained in a few days on a single GPU, allowing rapid experimentation and innovation. The current state-of-the-art in industry has advanced little beyond shallow techniques such as random forests and support vector machines, largely due to the difficulty of integrating world-class machine learning research with chemistry and pharmacology expertise.

Discovering a new small-molecule pharmaceutical requires navigating through a space of 10⁶⁰ synthesizable, drug-like molecules to find a compound that binds to, and thereby activates or inhibits, a single particular protein in the body. Such a drug candidate must deform its flexible protein target to facilitate binding interactions strong enough to overcome the reduced entropy of the ensemble and displaced interactions with water molecules. Even the smallest change to the drug candidate can radically impact its pharmacological properties, and the most elaborate first-principles simulations fail to consistently predict potency.

Variational AI is redefining the unit economics of drug discovery. We are pushing the state-of-the-art in machine learning, integrated with cheminformatics expertise, to radically accelerate the development of promising drug candidates for diseases ranging from cancer to COVID-19. Our small team of machine learning researchers and chemists is changing the massive pharmaceutical industry for the better.

We are looking for experienced software developers with machine learning/data science skills to join the team full-time. You will help us implement, test, characterize, and refine novel elements of a machine learning architecture designed from the ground up to optimize the properties of small-molecule drugs; continually improve the robustness of our existing code base; and apply our pipeline to new drug targets.

Here is the background we’re looking for:

• Ph.D. in machine learning or related discipline;
• Extensive publication record in top conferences (NeurIPS, ICML, ICLR, CVPR, etc.);
• Five or more years’ experience developing robust code on larger projects, including code review, refactoring, unit testing, version control, etc.;
• Expertise in Python and PyTorch;
• Intellectual curiosity and drive to excel.

We are an equal opportunity employer and enthusiastically welcome applications from women, BIPOC, and members of underrepresented communities and groups. Compensation is a competitive mix of cash and options. We prioritize expertise and passion over where you decide to live and work. Please send resumes/CVs to info@variational.ai.