MTS, Machine Learning

What you’ll do:

Develop machine learning models to predict molecular properties from chemical structures

Develop novel algorithms for generating ideas for new molecules

Build agents that can synthesize complex information from drug programs and apply that information strategically toward molecular optimization

Get your hands dirty by diving deep into our unique, proprietary dataset to iterate on modeling ideas and improve model performance

Collaborate closely with chemists and software engineers to integrate models into our software platform, which is used by drug discovery scientists across the industry

Build and optimize scalable infrastructure for model training, deployment, and monitoring

Engage directly with our scientific users, incorporating their feedback into the product

Contribute meaningfully to product strategy and company direction

Who you are:

You have 4+ years of experience as a Machine Learning Scientist, Machine Learning Engineer, Data Scientist, or similar role

You have a strong scientific background, ideally with a PhD in chemistry, biology, physics, or a related field

You have expertise in machine learning fundamentals, deep learning architectures, and evaluation approaches

You are proficient in standard Python-based ML frameworks (e.g. PyTorch, TensorFlow, scikit-learn)

You are comfortable writing high-quality, reusable code and productionizing models for serving in the cloud

You are excited to dive deep into the science and practice of drug discovery

You have exceptional written and oral communication skills

Preferred experience:

You have graduate-level knowledge of cell / molecular biology or biochemistry, and experience collaborating with wet lab scientists

Experience with omics modeling (transcriptomics, proteomics, metabolomics, etc)

Experience with high-content screening and signal processing from microscopy data