Machine Learning Researcher

Machine Learning Researcher

Internal Job Title: Member of Technical Staff
San Francisco Bay Area (On Site)
Up to $250K Generous Equity Benefits
Sponsorship Offered

With the life sciences industry spending over $12Bn a year on toxicology assessments alone, what if traditional lab experiments could be shifted to in silico?

How about if we could get better results, faster and at a fraction of the current spend?

Charter:

• Be a founding member of a team setting out to build the first accurate AI systems for replacing lab and animal toxicity experiments with AI models

Opportunity:

• Define the core end-to-end ML/AI system: wetlab data creation and data cleaning/processing; model architecture, training, and inference; compute infrastructure and model deployment
• Lead the research & development of novel models for understanding the relationship between chemistry and biology
• Architect and scale large models pre-trained on paired chemistry and biological images
• Set the foundation of a research culture which will grow to become the OpenAI for chemistry / biology
• Become a research leader in novel and underserved areas: molecular graph representations, contrastive learning for chemistry / biology, semi-supervised learning on biological images, generative diffusion for biology
• Grow as an entrepreneur as well as an engineer by building things from 0 to 1 while creating incredible value for scientists

You'll excel if you have experience in the following areas:

• Multi-modal ML or unsupervised / self-supervised learning with image data modalities
• End to end applied computer vision research
• Deep learning R&D applied to non standard, thorny modeling problems
• Deep learning for chemistry; especially pre-training, multi-modal training, and molecular property prediction
• Machine learning with cell imaging data

What we look for:

• Has done at least one piece of work, in industry or in academia, that shows exceptional machine learning talent
• Strong engineering abilities (writing Pytorch NN code, working with data in numpy / pandas, interacting with training and inference pipelines, and writing more general software in Python and interacting with the cloud)
• Extremely high potential to become a leader in the field of ML/AI research
• Demonstrates extreme, obsessive curiosity for both the science and business
• High ownership and agency, extremely ambitious

Keywords: Machine Learning, Deep Learning, Artificial Intelligence, AI, Biotechnology, Drug Discovery, Drug Development