Applied AI Researcher, System Self-Improvement

🇺🇸 San Francisco, California
$2K - $3K Annual
Posted 7 months ago
Expires June 9, 2026

ABOUT DISTYL AI

Distyl is an applied AI technology company partnering with the world’s most ambitious institutions to rearchitect critical operations for the frontier of AI. Our customers include the largest companies in telecom, healthcare, insurance, manufacturing, consumer goods, and global social organizations.

We research and deploy technologies that power AI-native operations — both for our partners and for Distyl itself. Our work spans research into self-constructing systems, the development of the most reliable execution of AI systems, and products that transform mission-critical workflows. As a result, Distyl's technologies affect some of the world's largest operations — from hundreds of millions of consumer interactions to tens of millions of supply chain transactions and millions of patient journeys.

Distyl is backed by leading investors including Lightspeed Venture Partners, Khosla Ventures, Coatue, DST Global, and the board-members of 20+ F500s. The results reflect this approach: a 100% production deployment success rate for our customers and one of the few enterprise AI companies to run a profitable business.

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.

Our researchers come from many academic backgrounds but have strong research track records, operate in an AI-native way, and would be bored staying on the rails of a traditional research org.

KEY 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:...

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