Tech Stack

Description

You will build greenfield machine learning models and algorithms to power drug discovery, working in a fast-paced interdisciplinary team to unlock new predictive capabilities in computational biology and chemistry.

Requirements

• PhD or equivalent practical experience in a technical field
• Proven track record in machine learning using deep learning techniques
• Strong knowledge of linear algebra, calculus, and statistics
• Experience with ML frameworks such as JAX, PyTorch, or TensorFlow
• Experience with scientific software such as NumPy, SciPy

Responsibilities

• Contribute to research directions in ML by applying algorithms to drug discovery
• Identify and create novel ML techniques and required data for training
• Develop architectures and training algorithms of ML models
• Analyze and tune experimental results to inform future directions
• Implement and scale training and inference engineering frameworks