Principal Machine Learning Engineer, Agentic AI

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 in the Agentic AI team, you will: 

• Leverage frameworks like AgengSDK, 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 on the cutting edge of agentic AI emerging paradigms, driving product innovation

• Serve as the focal point for applied science projects, driving alignment on timelines, and prioritization

• Continuously refine processes for experimentation, A/B testing, and production rollouts to balance rapid innovation with reliability and responsible deployment.

This role has been categorized as a Remote position. “Remote” employees do not have a permanent corporate office workplace and, instead, work from a physical location of their choice, which must be identified to the Company. U.S. employees may live in any of the 50 United States, with limited exceptions.

In California, Colorado, Connecticut, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, Nevada, New Jersey, New York, Rhode Island, Vermont, Washington state, and Washington DC the standard base pay range for this role is $199,000.00 - $318,000.00 Annually. This base pay range is specific to California, Colorado, Connecticut, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, Nevada, New Jersey, New York, Rhode Island, Vermont, Washington state, and Washington DC and may not be applicable to other locations.

In addition to a competitive base salary this position is also eligible for equity awards based on factors such as experience, performance and location. Actual amounts will vary depending on experience, performance and location.

Who you are

As a Principal Machine Learning Engineer, you are a roll-up-the-sleeves and get-it-done engineer who can marry state-of-the-art technology (i.e., LLM models, either from OpenAI or open source) with large-scale engineering. We are looking for someone who has:

• A master's degree or above,  equivalent experience in Computer Science, Electrical Engineering, or a related field with emphasis on foundational LLM, agentic AI,  reinforcement learning, AI planning, or natural language processing

• 7+ years of hands-on work building large-scale, high-impact solutions—ideally in the most recent two years building agent-based systems, multi-agent collaboration, or similar paradigms

• Experience developing dialogue systems capable of long conversations, multi-step reasoning, context-rich decision-making

• Experience deploying and scaling AI services capable of handling hundreds of millions of daily interactions with high availability, low latency, and robust fault tolerance

• A track record of publishing high-impact research in top AI/ML venue