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Zillow

Principal Machine Learning Engineer

Zillow · United States

  • Hybrid
  • Full-time
  • $265,500 / year
  • United States

Job highlights

  • Lead AI platform architecture and roadmap.
  • Build scalable, high-availability agent systems.
  • Drive cross-organizational execution and influence.
  • Mentor senior engineering talent.
  • Shape AI engineering culture.

About the role

About The Team

Zillow 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.

Compensation & Benefits

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.

Key skills/competency

  • Machine Learning Engineering
  • Agentic Systems
  • Platform Engineering
  • Distributed Systems Architecture
  • Python
  • Data Processing
  • Cloud Infrastructure (AWS)
  • Technical Leadership
  • System Design
  • Large-Scale Systems

Skills & topics

  • Principal Machine Learning Engineer
  • Machine Learning
  • AI
  • Agentic Systems
  • LLM
  • Platform Engineering
  • Data Infrastructure
  • Python
  • AWS
  • Technical Leadership

How to get hired

  • Tailor your resume: Highlight experience with agentic systems, LLMs, and large-scale ML infrastructure.
  • Showcase leadership: Emphasize your experience setting technical direction and driving cross-organizational projects.
  • Quantify achievements: Use numbers to demonstrate impact in scaling systems and delivering results.
  • Prepare for technical deep dives: Be ready to discuss system design, architecture, and failure modes.
  • Understand Zillow's mission: Connect your experience to Zillow's goal of reimagining real estate.

Technical preparation

Master Python and agentic frameworks.,Deep dive into distributed systems design.,Prepare to discuss large-scale data pipelines.,Review AWS best practices for ML.

Behavioral questions

Describe a complex cross-team initiative you led.,How do you balance innovation with production stability?,Share an example of mentoring senior engineers.,Explain a difficult technical trade-off you managed.

Frequently asked questions

What kind of experience does Zillow look for in a Principal Machine Learning Engineer?
Zillow seeks candidates with over 10 years of experience in building, scaling, and operating large-scale data and ML infrastructure, including production-grade pipelines and model-serving layers. Specifically, 1-2 years should involve shipping agent-based or LLM-powered systems. Strong technical leadership experience across multiple organizations (3+ years) is also crucial.
What are the key technical skills required for this role at Zillow?
Expert-level Python is essential, along with deep experience in agentic frameworks like LangGraph, LangChain, Agents SDK, or AutoGen. Proficiency in large-scale data processing (Spark, Databricks, Airflow, Temporal), vector stores, and cloud infrastructure, particularly AWS, is required. A background in distributed systems architecture and operational excellence is also key.
How does Zillow approach remote work for this Principal Machine Learning Engineer position?
This position is categorized as a Remote role. Remote employees do not have a permanent corporate office and can work from a chosen physical location, which must be identified to the company. U.S. employees can live in any of the 50 states, with limited exceptions.
What is the typical salary range for a Principal Machine Learning Engineer at Zillow in specific US locations?
For roles in California, Connecticut, Maryland, Massachusetts, New Jersey, New York, Washington state, and Washington DC, the base pay range is $204,400.00 - $326,600.00 annually. For Colorado, Hawaii, Illinois, Minnesota, Nevada, Ohio, Rhode Island, and Vermont, the range is $194,200.00 - $310,200.00 annually. Actual compensation may vary based on experience, performance, and location.
What does 'agentic systems expertise' mean for this Principal Machine Learning Engineer role at Zillow?
Agentic systems expertise means having hands-on experience designing and shipping agentic AI in production. This includes understanding orchestration, tool use, memory and context engineering, retrieval methods (embeddings, hybrid search, ranking), and evaluation. It also involves knowing how LLM-based systems can fail in production and how to engineer solutions around those failures.
How does Zillow foster technical leadership and growth for senior engineers?
Zillow encourages senior technical talent growth by having Principal Engineers mentor Senior and Staff engineers. This involves raising the bar on technical judgment, architecture decisions, and actively shaping the engineering culture of the organization.
What is the company culture like at Zillow for engineers?
Zillow aims to create an innovative, inclusive, and engaging culture where employees are empowered to grow. They are recognized as a great workplace, emphasizing innovation, customer support, and career advancement. The company values equal employment opportunity and fosters an inclusive environment.