About the job
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.
Responsibilities
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.
Qualifications
Minimum
Experience: 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.
Foundational ML & AI Expertise: 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)
Technical Stack: 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.
Leadership & Influence: Proven ability to build strong cross-functional relationships. You excel at leading collaborative efforts, creating buy-in for your architectural vision, and driving execution across matrixed teams.
Exceptional Communicator: Excellent verbal and written communication skills, with a track record of clearly articulating technical trade-offs to both engineering peers and executive leadership.
Engineering Rigor: Deep understanding of software design patterns, distributed systems architecture, and operational excellence (CI/CD, monitoring, A/B testing).
Agility: Comfort operating in a fast-paced, sometimes ambiguous "startup-like" environment within a larger enterprise, embracing a "build, learn, and pivot" mentality.
Preferred
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.