Develop robust autonomous software & ML Infrastructure using thoughtful architecture design, unit testing, integration testing, profiling, and collaboration.

Projects to which you may contribute:

Control Pathfinding - realtime autonomous decision making at the edge, using differentiable physics simulation inference, automated reasoning, state estimation, optimization, and machine learning

Autonomous Learning - updating physics models based on empirical observations, probabilistic event modeling, fault detection, quantifying the quality of empirical/prediction data, attributing error causes, etc. Generally, improving system performance as it gathers experience

Weather Prediction - forecasting, with contexts ranging from having an internet connection with forecast API access, to no internet connection and only using locally observable information to forecast weather

AI Solver Infrastructure - developing the infrastructure that makes it easy to do automated physics inference, optimization, learning, etc.