Senior 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 Senior Machine Learning Engineer for the Agentic AI team to develop advanced multimodal customer experiences. They will be hands-on in prototyping ideas, training models, evaluating, and deploying them to Zillow's highly scalable infrastructure platforms. They’ll be building vision and language understanding models with deep reasoning and reinforcement learning to handle AI agent decision-making. 

As a Senior Machine Learning Engineer in the Agentic AI team, you will: 

• Leverage agentic frameworks like Agents SDK, or LangGraph to design, prototype, and develop multi-agent systems that are capable of highly autonomous and context-aware interactions

• Leverage frontier GenAI models, including vision, language, and voice models, to build agentic prototypes and later convert them into agentic products for millions of Zillow customers.

• Exploit a highly scalable platform for training and fine-tuning OSS models to adapt them to the real estate domain.

• Mentor and guide other engineers and partners in using the right technologies for agentic AI solutions, and foster a culture of innovation and responsible AI usage

• Distill complex research findings collected through surveys and AI model architectures into actionable insights for diverse audiences—including executives

• Remain on the cutting edge of agentic AI emerging paradigms, implement papers with code, and drive product innovation

• Serve as the focal point for projects, independently 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 $168,600.00 - $269,400.00 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 Senior Machine Learning Engineer, you are a roll-up-the-sleeves and get-it-done engineer who can marry state-of-the-art technology 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 building products using frontier multimodal LLMs

• Expertise in agentic AI, pretraining, fine-tuning, and reinforcement learning of vision, language, and voice models

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

• Experience deploying and scaling AI services capable of handling hundreds of millions of daily interactions with hig