Machine Learning Engineer, Agentic AI

Zillow Zillow · Consumer · United States · Remote

Machine Learning Engineer on the Agentic AI team, focusing on designing, building, and productionizing domain-specialized AI capabilities for Zillow's real estate experiences. The role involves advancing multi-step reasoning, structured synthesis, and tool-grounded intelligence for AI agents operating in live customer environments.

What you'd actually do

  1. Design and build scalable AI infra and services to power agentic AI applications
  2. Develop advanced reasoning and agentic capabilities that enable AI agents to operate autonomously and adaptively in dynamic, real-world environments
  3. Implement monitoring, evaluation, and optimization processes to ensure reliability and responsiveness in production
  4. Stay at the forefront of agentic AI innovation, bringing emerging techniques into practical application to shape product direction.
  5. Collaborate closely with applied scientists, engineers, and product teams to translate experimental prototypes into robust production systems

Skills

Required

  • Python
  • TensorFlow
  • PyTorch
  • LangChain
  • LangGraph
  • building production ML systems and services
  • AI agent frameworks
  • orchestration
  • multi-step reasoning applications
  • designing and operating scalable, cloud-based ML infrastructure
  • working in cross-functional teams

Nice to have

  • Bachelor’s or Master’s in Computer Science or a related field

What the JD emphasized

  • production-grade AI systems
  • multi-step reasoning
  • tool-grounded execution
  • rigorous quality evaluation
  • AI agents
  • reasoning depth
  • domain intelligence
  • AI Assistant
  • reason
  • plan
  • act
  • judgment
  • domain-specialized AI capabilities
  • structured synthesis
  • tool-grounded intelligence
  • live customer environments
  • agentic AI applications
  • operate autonomously
  • adaptively
  • dynamic, real-world environments
  • monitoring, evaluation, and optimization processes
  • reliability and responsiveness in production
  • agentic AI innovation
  • practical application
  • shape product direction
  • experimental prototypes
  • robust production systems
  • distributed ML systems
  • scalable architecture
  • responsible AI deployment
  • hands-on builder
  • AI innovation
  • engineering excellence
  • cutting-edge ideas
  • production systems that scale
  • AI agent frameworks
  • orchestration
  • multi-step reasoning applications
  • scalable, cloud-based ML infrastructure
  • impactful AI-driven features

Other signals

  • agentic AI
  • multi-step reasoning
  • production-grade AI systems