Distyl AI develops AI native technologies for humans & AI to collaborate to power the operations of the Global Fortune 1000.

In just 24 months, we’ve rapidly grown to partner with some of the world’s largest enterprises—including F100 telecom, healthcare, manufacturing, insurance, and retail companies—delivering multiple AI deployments with $100M+ impact. Our platform, Distillery, along with our team of AI Engineers, Researchers, and Strategists, is pioneering AI-native systems of work, solving the most complex, high-stakes challenges at scale.

Distyl is founded and led by proven leaders from companies like Palantir, Apple, and top national laboratories. We work in deep partnership with OpenAI, jointly going-to-market at the largest enterprises and collaborating evaluating and testing the latest models. Backed by Lightspeed, Khosla, Coatue, industry leaders like Nat Friedman (former GitHub CEO), as well as board members of over 20+ F500s, Distyl is building the future of AI-powered enterprise operations.

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: 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 Require

• Experience Building Feedback-Driven Systems: You’ve built or studied systems that monitor, score, and adapt—evaluators, retrievers, iterative refinement loops, or performance dashboards that close the feedback loop.
• Experience Building with Models, Not Just Building Models: We develop intelligent systems using models rather than training or fine-tuning them. Ideal candidates have expertise in compound AI systems, agentic collaboration, and associated techniques (ensembling, ReAct, graph-of-thoughts, etc.).
• Proven Track Record of Research Results: Whether you’ve published in top journals, posted amazing work on twitter, or somewhere else we want to see what you've done.

What We Offer

• An opportunity to advance the cutting edge of LLM research and directly revolutionize work in the enterprise space.
• Ownership of high-impact research projects, with the autonomy to explore novel approaches and solutions.
• Access to state-of-the-art AI models, real business problems, and proprietary data sets across a diverse range of real-world industries.
• Competitive salary and benefits package, including equity options, medical/dental/vision covered at 100% for you and your dependents, 401K plan, and perks such as commuter benefits and lunch provided in office.
• Be part of a mission-oriented company to create practical adoption during the biggest revolution in human productivity.
• A collaborative and intellectually stimulating environment that encourages innovation and personal growth.

If you are an innovative, ambitious, and driven individual looking to make a difference in the world of AI, we want to hear from you. Apply now to join our team as an Applied AI Researcher and help us shape the future of AI-driven solutions for enterprises across the globe.

Note: Distyl is a hybrid working environment and requires in office collaboration 3 days a week. We have offices in SF and NYC