[Remote] Principal Machine Learning Engineer (Memory & Context)

Note: The job is a remote job and is open to candidates in USA. Zillow is hiring a Principal Machine Learning Engineer on its Agentic AI team to build the memory and context capabilities of its real estate assistant. The role owns agent memory architecture, production context engineering and orchestration, evaluation frameworks, and technical leadership across teams.

Responsibilities

• Own the architecture of agent memory: what Zillow's assistant remembers about each user across conversations, and how memories are written, retrieved, updated, and retired
• Lead context engineering for production agents: assembling, prioritizing, and compressing context from conversation history, user memory, tools, and skills so every response is relevant, fast, and cost-efficient
• Build and orchestrate agents end to end, from prompt and context design to deployment and operation in production
• Define evaluation frameworks for memory and context quality, offline and online, and use them to drive product and technical decisions
• Stay on the cutting edge of emerging agentic paradigms, including memory architectures and long-context techniques, and convert them into tangible product innovation
• Lead complex, multi-team initiatives and communicate technical direction clearly to engineers, partner teams, and leadership

Skills

• A master's degree or above, or equivalent experience, in Computer Science, Electrical Engineering, or a related field
• 5+ years of experience deploying large-scale ML systems, including at least the most recent year building and shipping LLM-based agents in production
• Hands-on experience building agents end to end: orchestration, prompt engineering and optimization, and context engineering
• Experience evaluating agentic systems and using those results to improve them
• Proven technical leadership: you have influenced technical direction across teams and mentored other engineers
• Strong communication skills, including presenting to senior leadership
• Strong programming skills in Python and familiarity with agentic AI frameworks such as LangGraph, Agents SDK, or AutoGen
• Experience designing agent or user memory systems (long-term, episodic, or user-profile memory)
• Experience with dialogue systems that sustain long, multi-session conversations
• Personalization of AI assistants from conversation history
• Publications, patents, or open-source contributions related to memory, long-context models, or agents

Benefits

• Eligible for equity awards based on factors such as experience, performance and location.
• Most employees have the flexibility to work from wherever they’re most productive.

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