Applied AI Researcher, System Self-Improvement

Distyl is an applied AI technology company partnering with large institutions to rearchitect critical operations for the frontier of AI. The company is seeking an Applied AI Researcher for its System Self-Improvement team to design feedback-driven AI systems that can evaluate themselves, identify weaknesses, and continuously improve through reflection, retraining, and workflow adaptation. The role focuses on building compound AI systems, conducting research experiments, and demonstrating practical enterprise impact.

Responsibilities:

• The System Self-Improvement team builds architectures that continuously evaluate and enhance their own performance. Researchers design feedback-driven systems capable of detecting weaknesses, generating corrective hypotheses, and implementing their own improvements through reflection, retraining, or workflow adaptation. The goal: build AI systems that compound in capability through use
• Researchers in Self-Improvement study how systems can form self-models—understanding when, why, and how they succeed or fail. They explore reflective reasoning, reward modeling, and self-evaluation techniques to enable autonomous evolution. This work bridges reinforcement learning, interpretability, and meta-optimization to pioneer continuously learning enterprise systems