Building the first accurate AI systems for replacing lab and animal toxicity experiments with AI models.
Requirements
- writing Pytorch NN code
- working with data in numpy / pandas
- interacting with training and inference pipelines
- writing more general software in Python
- interacting with the cloud
- Novel usage and application of embeddings in applied research settings
- Deep learning research applied to non standard, thorny modeling problems
Responsibilities
- 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 pretrained on paired chemistry and biological images
- Applied research on optimizing, aggregating, and pooling embeddings
- Become a research leader in novel and underserved areas: molecular graph representations, contrastive learning for chem/bio, semi-supervised learning on biological images, generative diffusion for biology
- Ship insanely great technology + products
- Architects of ML systems from data generation, data processing, ML infra, training, and evaluation
Other
- Be a founding member of a team
- High agency is critical: they see what’s important and they do it.
- Grow as an entrepreneur as well as an engineer by building things from 0 to 1 while creating incredible value for scientists
- Has done at least one piece of work, in industry or in academia, that shows exceptional machine learning talent
- Extremely high potential to become a leader in the field of ML/AI research
