Principal AI/ML Researcher / Engineer In Bayesian, Large Foundational Systems, and Distributional Reinforcement Learning

15+ years of technical experience in Applied Machine Learning, including producing code and deploying production systems.

, with expertise in AI/ML frameworks (e.g., TensorFlow, PyTorch).

Proven experience with Bayesian Neural Networks, Bayesian Learning, and Reinforcement Learning.

Experience with building scalable AI/ML systems using technologies like

, and distributed architectures.

Familiarity with advanced ML techniques, including Mixture of Models, Ensemble Techniques, multitask learning, and sharded architectures.

Principal AI/ML Researcher and Engineer

Distributional Reinforcement Learning (RL)

to lead the advanced research and development of cutting-edge intelligence AI models.

These systems will integrate foundational Bayesian frameworks with advanced architectures, including

Additionally, the role involves innovating ways to interoperate and integrate

into the Bayesian frameworks to create a seamless foundational model fabric that synergizes with diverse model ecosystems.The role will require ensuring these models and supporting systems perform efficiently at