AI Engineer — Reinforcement Learning

Yutori is reimagining how people interact with the web by building AI agents that can reliably do everyday digital tasks. We are building the entire stack to be agent-first, from training our own models to generative product interfaces. Towards this goal, we are looking for a member of the AI technical staff to join the founding team. Someone technically strongly, and excited about building superhuman AI agents that take actions on the web. Our founders — Devi Parikh, Abhishek Das, Dhruv Batra — have decades of experience in AI research and product spanning generative, multimodal and embodied AI at Meta. Our team combines AI experience with design-minded product thinking to build and deliver on Yutori’s mission. Yutori is backed by a stellar set of visionary investors — Elad Gil, Sarah Guo, Jeff Dean, Fei-Fei Li, Amjad Masad, Guillermo Rauch, Akshay Kothari, Soleio, Oliver Cameron, Julien Chaumond, Logan Kilpatrick, Bryan McCann, Vladlen Koltun, Jamie Cuffe, Michele Catasta, etc. Responsibilities: Build a superhuman generalist web-agent Scale infra, data, algorithms for large-scale distributed async reinforcement learning with multimodal LLMs acting in web environments Work closely with product engineers to translate cutting-edge AI capabilities into elegant and reliable product experiences. What we’re looking for: Experience with large-scale RL, ideally for post-training multimodal LLMs Experience building distributed systems for RL (balancing trainer, environment, actor workloads) Experience with ML infrastructure (GPU clusters) and supporting networking (NCCL) High IQ, high EQ, high agency, high craftsmanship, low ego. Proactive, clear communication. Benefits and perks: Competitive salary and equity Visa sponsorship and relocation stipend to bring you to SF Generous health, dental, vision insurance for you and your dependents 20 days of paid time off per year Work laptop and budget to set up your work office Daily team lunches Commuter benefits Small, focused team of high-potential individuals. In-person in SF.

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