Agentic AI, Principal Machine Learning Engineer

Zillow Group, Inc.

$194K — $326K *
US-AnywhereRemote in United States
Consumer Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Master's degree in Computer Science, Electrical Engineering, or equivalent experience, focusing on multimodal LLM products.
  • 5+ years of deploying large-scale machine learning models, with 2-3 years in agent-based systems.
  • Experience with dialogue systems for long conversations and context-aware responses.
  • Capability to build AI services handling millions of daily interactions with reliability.
  • Familiarity with agentic AI frameworks like LangGraph and production ML infrastructure.
  • Strong communication skills for influencing technical direction and presenting to leadership.

Responsibilities

  • Develop large-scale multimodal AI experiences for millions of customers.
  • Design interaction modes such as Voice AI and Deep Research.
  • Create robust evaluation frameworks and safety measures for AI agents.
  • Research and apply emerging agentic paradigms for product innovation.
  • Lead cross-functional initiatives between applied research and scalable engineering.
  • Convert complex research and architecture into actionable insights for diverse audiences.

Benefits

  • Remote work flexibility from any location within the U.S.
  • Equity awards based on experience and performance.
Full Job Description

About the role

As a Principal Machine Learning Engineer on the Agentic Artificial Intelligence team, you will get to: 

  • Develop large-scale, fault-tolerant multimodal agentic experiences that reach millions of customers

  • Design and develop multiple agent interaction modes, including Voice AI and Deep Research. 

  • Pioneer robust evaluation frameworks, tracing systems, and safety guardrails to ensure our highly-visible AI agents remain trustworthy and responsible

  • Remain on the cutting edge of emerging agentic paradigms and convert them into tangible product innovation

  • Lead complex, multi-team initiatives, bridging the gap between applied research and highly scalable engineering

  • Distill complex research findings and AI system architectures into actionable insights for a diverse audience, including executives and cross-functional partner teams

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 $204,400.00 - $326,600.00 annually. This base pay range is specific to these locations and may not be applicable to other locations. In Colorado, Hawaii, Illinois, Maine, Minnesota, Nevada, Ohio, Rhode Island, Vermont, and Virginia the standard base pay range for this role is $194,200.00 - $310,200.00 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

As a Principal Machine Learning Engineer, you are a roll-up-the-sleeves and get-it-done technical leader 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 emphasis on building products using frontier multimodal LLMs

  • 5+ years of experience with a proven track record of deploying large-scale ML models, with the most recent 2-3 years building agent-based systems, multi-agent collaboration, or similar paradigms

  • Experience developing engaging dialogue systems capable of long conversations, context-aware tool selection, and compliant response generation

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

  • Familiarity with various agentic AI frameworks, such as LangGraph, Agents SDK, AutoGen, and production ML infrastructure

  • A track record of writing articles, patents, and publishing high-impact research is a strong plus

  • Strong communication skills, with the ability to influence technical direction across teams and present to executive leadership

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