Senior Machine Learning Engineer

Zillow

1d•Remote

About The Position

Zillow is seeking a highly experienced, product-minded Senior Machine Learning Engineer to anchor our Agentic Data Foundations team within the broader Agentic Data Platform organization. In this role, you will be the bridge between our core data platforms and the AI teams building Zillow’s next-generation customer experiences. You will design and build the highly scalable, robust foundational infrastructure that empowers our AI teams. We need a "roll-up-your-sleeves" technical leader who thrives in ambiguity, holds a high bar for production engineering, and possesses the ability to align multiple teams around a shared technical vision. As a Senior Machine Learning Engineer on the Agentic Data Foundations team, you will: Architect and Build: Lead the design, prototyping, and deployment of scalable machine learning infrastructure that can power Zillow AI Mode. Bridge and Partner: Serve as a critical technical liaison between the Agentic Data Platform and applied AI teams. You will collaborate closely with scientists, engineers, and product partners to understand their dependencies and deliver the data foundations they need to innovate rapidly. Influence and Align: Act as a technical anchor for the team. You will drive alignment on timelines, architectures, and prioritization across different organizations, successfully influencing technical direction without requiring direct authority. Scale for Impact: Deploy and optimize capabilities in production environments, ensuring high availability, low latency, and efficient resource utilization capable of handling massive scale. Mentor and Elevate: Foster a culture of rapid innovation, frugality, and engineering excellence. You will mentor other engineers, guiding them in using the right technologies and establishing best practices. Distill Complexity: Translate complex ML infrastructure designs and ambiguous customer problems into clear, actionable insights for diverse audiences, including leadership and non-technical stakeholders. 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.

Requirements

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.
Familiarity with agentic patterns including orchestration, tool use, skill-based architectures, memory, and retrieval strategies (embeddings, hybrid search, ranking).
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.
Excel at leading collaborative efforts, creating buy-in for your architectural vision, and driving execution across matrixed teams.
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.

Nice To Haves

Advanced degree (M.S. or Ph.D.) in Computer Science, Machine Learning, or a related field.
Experience building foundational infrastructure for agentic systems or real-time AI applications.
Experience with regulated, private, or sensitive data at scale.

Responsibilities

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.
Act as a technical anchor for the team, driving alignment on timelines, architectures, and prioritization across different organizations.
Deploy and optimize capabilities in production environments, ensuring high availability, low latency, and efficient resource utilization capable of handling massive scale.
Foster a culture of rapid innovation, frugality, and engineering excellence.
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.