Applied Artificial Intelligence Researcher (Multi-Agent Systems)

• 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
• The Multi-Agent Systems team focuses on designing architectures in which multiple agents coordinate to solve problems that require structured interaction across multiple reasoning processes
• Researchers build systems that structure communication, route information, and coordinate decision-making across agents operating with different views of the problem
• Researchers in Multi-Agent Systems investigate the interaction patterns that govern how agents collaborate
• They study how agents exchange information, critique and refine each other’s reasoning, and coordinate execution across complex workflows
• Their work identifies the mechanics behind effective communication, delegation, and coordination, in effect establishing the design language for how systems of agents can operate as cohesive, high-performing teams, with capabilities that arise from interaction rather than individual performance

Benefits

• Equity options and healthcare
• Collaborative and supportive work environment
• Strong focus on personal and professional growth- Uses AI Every Day: Before you can revolutionize someone else’s workflow, you need to revolutionize yours. You should be using tools like ChatGPT, Cursor, and Perplexity to accelerate your workflow
• Excited about making foundational advancements in how agents coordinate, reason and collaborate
• 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
• Experience with agent orchestration, communication protocols, evaluator agents, or systems where multiple agents interact to exchange information, critique reasoning, and coordinate decisions over time
• Built or studied systems where multiple agents collaborate through structured communication, delegation, critique, or iterative coordination
• Strong Programming and Data Analysis Skills: While you might not consider yourself a software engineer you need to be able to build prototypes of your ideas and then perform the experiments to prove the effectiveness to a F500 Head of AI
• Biases Towards Showing vs Telling: Our customers want to see the power of AI today vs discuss the most elegant idea that will take 5 years to realize
• Experience with research in related fields, such as multi-agent reinforcement learning (MARL), graph neural networks (GNNs), knowledge graphs, mixed-initiative planning, etc