AI Engineer — Reinforcement Learning

Yutori· San Francisco, California, United States· ashby· veröffentlicht 26.03.2025
Muss:AIPrincipal
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.