Machine Learning Engineer, Agentic AI – User Understanding

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 Machine Learning Engineer for the Agentic AI team to develop advanced agentic customer experiences. You will be hands-on in prototyping ideas, training large language models (LLMs), evaluating, and deploying them to Zillow’s highly scalable infrastructure platforms. You will develop models to gain deeper insights into user behavior and manage the decision-making processes of AI agents.

You Will Get To:

• Build and maintain data pipelines for LLM (Large Language Model) training and evaluation, curate user-understanding signals (such as intents, preferences, and behavioral features), and ensure data quality, privacy, and proper dataset management.

• Develop and manage labeling and feedback loops, including heuristics, annotation jobs, and prompt-based labeling, to create high-quality corpora, collaborating with Data Engineering and Applied Science partners to improve data coverage and reduce noise.

• Design, prototype, and ship to production agentic AI solutions, including multi-agent systems using frameworks like LangGraph, and implement context-aware features in partnership with senior engineers.

• Implement an evaluation framework to measure model quality on offline test sets (accuracy, bias, safety, user-intent coverage), and build dashboards to track improvements over time.

• Lead and contribute to experimentation by implementing metrics, A/B tests, and monitoring, helping to harden prototypes for reliable rollouts.

• Collaborate with senior engineers and cross-functional partners to select the right technologies, participate in code reviews, and share best practices (including mentoring interns or new hires as needed).

• Summarize research findings and model evaluations into clear write-ups and demos for the team and cross-functional stakeholders.

• Stay current on emerging agentic AI paradigms, implement paper-inspired proofs of concept, and contribute insights to the team roadmap.

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, Connecticut, Maryland, Massachusetts, New Jersey, New York, Washington state, and Washington DC the standard base pay range for this role is $145,500.00 - $232,500.00 annually. This base pay range is specific to these locations and may not be applicable to other locations. In Colorado, Hawaii, Illinois, Minnesota, Nevada, Ohio, Rhode Island, and Vermont the standard base pay range for this role is $138,300.00 - $220,900.00 annually. The base pay range is specific to these locations 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. Employees in this role will not be paid below the salary threshold for exempt employees in the state where they reside.

Who you are

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, or equivalent experience in Computer Science, Electrical Engineering, or a related field, with an emphasis on building products using frontier multimodal LLMs (Large Language Models).

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

• 3+ years of hands-on experience building large-scale, high-impact solutions, ideally with recent experience in agent-based systems, multi-