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Zillow

Principal Machine Learning Engineer

Reposted 2 Hours Ago
Remote
Hiring Remotely in USA
194K-327K Annually
Expert/Leader
Remote
Hiring Remotely in USA
194K-327K Annually
Expert/Leader
The Principal Machine Learning Engineer will define technical direction, architect scalable systems, lead cross-organizational initiatives, mentor engineers, and communicate effectively at all levels.
The summary above was generated by AI

About the teamZillow is building the next generation of AI experiences for the millions of customers who are navigating one of the most important decisions of their lives. Agentic Data Platform's(ADP) mission is to power Zillow's agentic future by exploring and delivering bleeding-edge foundational platform capabilities that make agentic systems scalable across Zillow.
Agentic Data Platform(ADP) operates as a small, high-leverage 'startup-within-the-company' to bridge Zillow's broader platform and the Agentic AI organization that ships customer-facing agentic experiences at scale. We are looking for a Principal engineer with strong, senior-level leadership - someone who sets strategic and technical direction for ADP, and partners deeply across Agentic AI and the broader platform orgs.

About the role

As a Principal Machine Learning Engineer in the Agentic Data Platform organization, you will:

  • Set the technical direction. Define and own the multi-quarter architecture roadmap for the agentic data foundations (Context engineering, Agentic memory, and AI workflows) that power Zillow's agentic experiences.

  • Architect and ship at scale. Design, prototype, and ship systems that handle hundreds of millions of agent interactions with high availability, low latency, and predictable cost. Stay hands-on in code and production when it matters.

  • Drive cross-organization execution. Lead complex, multi-team initiatives across Agentic AI and Platform teams - aligning on architecture, surfacing dependencies, and driving outcomes through influence rather than direct authority.

  • Communicate to every level. Translate complex platform trade-offs, ambiguous customer problems, and emerging agentic paradigms into clear, actionable insights for engineering peers, product partners, Directors, and VPs

  • Grow senior technical talent. Mentor Senior and Staff engineers, raise the bar on technical judgment and architecture decisions, and shape the engineering culture of the org.

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, Minnesota, Nevada, Ohio, Rhode Island, and Vermont 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

You've shipped agentic systems in production and you've built large-scale platform infrastructure and you know the failure modes specific to doing both at once, what's worth abstracting, and what isn't yet. You move comfortably between architecting a multi-quarter platform investment and writing the prototype that proves it works.

You resist premature platform building: you ship the smallest foundation that meets a real need, then harden the pattern once it's clear. You think in production grade defaults — observability, evaluation, safety, latency, cost — and you raise the bar quietly through the systems and docs you leave behind. You operate well in ambiguity, earn alignment across science, engineering, and product through clear writing and sharp design, and lead from the front: whiteboard, design doc, production code.

Our ideal candidate meets the following requirements
  • Experience. 10+ years building, scaling, and operating large-scale data and ML infrastructure (production-grade pipelines, feature stores, and model-serving layers), with 1 to 2 of those recent years shipping agent-based or LLM-powered systems to production. 3+ years as a technical leader spanning multiple organizations.

  • Agentic systems expertise. Hands-on experience designing and shipping agentic AI in production — orchestration, tool use, memory and context engineering, retrieval (embeddings, hybrid search, ranking) and evaluation. You understand how LLM-based systems fail in production and how to engineer around it.

  • Platform Fluency. Platform engineering background in scaling and abstracting large-scale data and ML infrastructure. Expert in distributed systems architecture, and operational excellence. You’ve designed systems that hold up under massive scale and tight SLOs.

  • Technical stack. Expert-level Python; deep experience with agentic frameworks (LangGraph, LangChain, Agents SDK, AutoGen), large-scale data processing (Spark, Databricks, Airflow, Temporal), vector stores, and cloud Infrastructure (AWS preferred).

  • Cross-organization leadership and communication. Proven ability to set technical direction across organizational boundaries, build trust with engineering, science, and product leaders, and articulate complex trade-offs clearly to engineering peers and executives. You drive outcomes through influence, not authority.

Nice to have
  • Advanced degree (M.S. or Ph.D.) in Computer Science, Machine Learning, or a related field, with emphasis on building distributed systems and AI.

  • Experience building data platform for agentic systems or real‑time AI applications.

  • Experience working with regulated, private, or sensitive data at scale.

  • Experience designing evaluation, tracing, or safety frameworks for LLM‑based production systems.

Get to know us

At Zillow, we’re reimagining how people move—through the real estate market and through their careers. As the most-visited real estate platform in the U.S., we help customers navigate buying, selling, financing and renting with greater ease and confidence. Whether you're working in tech, sales, operations, or design, you’ll be part of a company that's reshaping an industry and helping more people make home a reality.

Zillow is honored to be recognized among the best workplaces in the country. Zillow was named one of FORTUNE 100 Best Companies to Work For® in 2025, and included on the PEOPLE Companies That Care® 2025 list, reflecting our commitment to creating an innovative, inclusive, and engaging culture where employees are empowered to grow.

No matter where you sit in the organization, your work will help drive innovation, support our customers, and move the industry—and your career—forward, together.

Zillow Group is an equal opportunity employer committed to fostering an inclusive, innovative environment with the best employees. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please contact your recruiter directly.

Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable state and local law.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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