• Location
    • San Francisco
  • Date Posted
  • May. 30, 2021
  • Function
  • Research & Science
  • Sector
  • AI/ML

Responsible for coming up with new techniques in unsupervised learning, dataset augmentation and deep reinforcement learning that can be applied to automating various parts of the AI development workflow.

Candidates will need to have a PhD preferably in Artificial Intelligence or Machine Learning. We are looking for people who have done research / published papers in one of the following areas:

Unsupervised Learning

Generative Modeling

Deep Neural Networks

Deep Reinforcement Learning

Generative Adversarial Networks

Causal Reasoning

Ideal candidates would be able to rapidly iterate on new ideas with engineers, potentially publish at top conferences and be able to write code.