Senior Machine Learning Engineer

Zillow

Senior Machine Learning Engineer at Zillow designing and building scalable infrastructure for AI teams. Collaborating across teams to align technical direction and optimize production capabilities.

Posted 4/24/2026full-timeRemote • California, Connecticut, District of Columbia, Maryland, Massachusetts, New Jersey, New York, Washington • 🇺🇸 United StatesSenior💰 $171,700 - $274,300 per yearWebsite

Tech Stack

Tools & technologies

AirflowAWSCloudDistributed SystemsPythonSpark

About the role

Key responsibilities & impact

Lead the design, prototyping, and deployment of scalable machine learning infrastructure that can power Zillow AI Mode.
Serve as a critical technical liaison between the Agentic Data Platform and applied AI teams.
Collaborate closely with scientists, engineers, and product partners to understand their dependencies and deliver the data foundations they need to innovate rapidly.
Drive alignment on timelines, architectures, and prioritization across different organizations, influencing technical direction without requiring direct authority.
Deploy and optimize capabilities in production environments, ensuring high availability, low latency, and efficient resource utilization capable of handling massive scale.
Mentor other engineers, guiding them in using the right technologies and establishing best practices.
Translate complex ML infrastructure designs and ambiguous customer problems into clear, actionable insights for diverse audiences, including leadership and non-technical stakeholders.

Requirements

What you’ll need

6+ years of hands-on expertise building, scaling, and operating large scale data and ML infrastructure, including production-grade pipelines, feature stores, model-serving layers or end-to-end ML systems.
Deep understanding of Machine Learning fundamentals and the production systems they require — data flows, serving infrastructure, observability, and evaluation.
Proficiency with agentic AI frameworks (e.g., LangGraph, LangChain, Agents SDK), large-scale data processing (Spark, Databricks, Airflow), cloud platforms (AWS preferred), and vector stores. Python required.
Proven ability to build strong cross-functional relationships.
Excellent verbal and written communication skills, with a track record of clearly articulating technical trade-offs to both engineering peers and executive leadership.
Deep understanding of software design patterns, distributed systems architecture, and operational excellence (CI/CD, monitoring, A/B testing).
Comfort operating in a fast-paced, sometimes ambiguous 'startup-like' environment within a larger enterprise, embracing a 'build, learn, and pivot' mentality.

Benefits

Comp & perks

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.

ATS Keywords

✓ Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learning infrastructuredata pipelinesfeature storesmodel-serving layersend-to-end ML systemsPythonsoftware design patternsdistributed systems architectureCI/CDA/B testing

Soft Skills

mentoringcross-functional relationshipsverbal communicationwritten communicationinfluencingcollaborationproblem-solvingtechnical directionarticulating technical trade-offsoperating in ambiguous environments