Principal Machine Learning Engineer, Agentic AI - GXC - Austin, TX
GXC
About The Team
The Agentic AI team at Zillow is at the forefront of transforming the real estate industry by helping millions of people use AI technologies to find their next home. We aim to redefine the home shopping and transaction experience by providing an always-on assistant that integrates deep user insights and sophisticated reasoning. By embedding domain knowledge and specialized expertise in these assistants, we empower home buyers and real estate professionals to gain efficiency while maintaining Zillow's competitive edge. This lean, customer-focused team comprises scientists and engineers working together to deliver a delightful customer experience. We strongly believe in accountability, collaboration, and transparency.
About The Role
Zillow is looking for a Principal Machine Learning Engineer on the Agentic AI team to develop advanced multimodal foundational technologies. They will be hands-on in prototyping ideas, evaluating, and deploying models to Zillow's highly scalable infrastructure platforms. They’ll be developing perception and language understanding, deep reasoning, and reinforcement learning to handle AI agent decision-making.
As a Principal Machine Learning Engineer on the Agentic AI team, you will:
Leverage frameworks like AgentSDK, and LangChain/LangGraph to design, prototype, and develop multi-agent systems that are capable of highly autonomous and context-aware interactions Leverage advanced GenAI models including reasoning models, real-time voice API, etc, to build agentic prototypes and later on convert them into product-level agentic skills and deploy to users. Have the mentality of “build, learn, and pivot”, and hold the high bar of shipping into production. Mentor and guide engineers in using the right technologies for agentic AI solutions and foster a culture of innovation and responsible AI usage Distill complex research findings and system designs into actionable insights for diverse audiences—including executives Remain o