Sobre esta vaga de Staff Applied Machine Learning Engineer na Zaimler
Zaimler · Presencial · San Mateo, CA
About zaimler
AI agents can't reason over data they don't understand. Enterprise data today is fragmented across dozens of systems with no shared context, meaning, or structure, and that's why most enterprise AI is failing. The shift from copilots to autonomous agents is creating an entirely new infrastructure layer, and we're building it.
zaimler is the context infrastructure for the agentic era: a platform that automatically discovers domain knowledge, maps relationships, and gives AI agents the semantic understanding to operate with precision at scale. Imagine knowledge graphs that support real-time inference, built for systems that need to reason, not just retrieve.
zaimler was founded by Biswajit Das (ex-VP Engineering, Truera), a Data Infra veteran and former Chief Architect at Visa, and Sofus Macskassy (ex-Director of Engineering, LinkedIn), who built one of the largest knowledge graphs in production in the industry at LinkedIn. We're growing and deploying with major enterprises across insurance, travel, and technology. If you want to build infrastructure that the next decade of enterprise AI runs on, we'd love to talk.
About the Role
This is a staff-level role for a seasoned AI/ML engineer who can operate at the intersection of research and production. You'll serve as the technical bridge between our research and applied engineering teams — translating cutting-edge ideas into robust, scalable systems while setting the strategic direction for how we train, evaluate, and deploy models. Deeply hands-on, but able to zoom out and set the agenda.
We're looking for someone who has been here before. Built the infra, shaped the strategy, and knows what good looks like at every layer of the ML stack.
What You Will be Doing
Prior Experience
Nice to Have
We value builders over résumés. If this role excites you but you don't check every box, we still want to hear from you. zaimler is an equal opportunity employer.
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