Applied AI Researcher, System Self-Improvement

• 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.

What we are looking for

At Distyl we’re pushing the envelope of AI utilization in enterprise. This requires creative researchers who don’t just want to drive incremental improvements on benchmarks or optimize an existing process but instead are looking to creatively redefine how software is used.