Principal Machine Learning Engineer, Memory & Context

Zillow

Confirmed live yesterday High trust
Remote

Quick summary

Work type
Remote
Location
Remote
Salary
$209,400–$334,600 / yr
Employment
Full-time
Posted
5 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $232k
This role $272k
$167k $353k
below market most similar roles pay here above market

This role pays more than 83% of similar roles. Most pay $208,462–$254,750 — the blue band above. At the midpoint, this role pays about $272k versus about $232k for comparable roles.

Based on 240 similar postings.

Employer

About Zillow

Zillow Group is a leading real estate and rental marketplace providing consumers with data, tools, and services to find, buy, sell, rent, and finance homes, and connecting buyers with agents and lenders. Industry: Real Estate Technology & Marketplace

Zillow currently has 49 open roles on FindRole.

Listed pay typically runs $164,400–$262,600 across 40 roles with salary data.

Most-posted roles

View all roles at Zillow

At a glance

TL;DR · Principal Machine Learning Engineer, Memory & Context

The Principal Machine Learning Engineer (Memory & Context) joins the Agentic AI team to advance Zillow’s agentic capabilities. This role involves shaping the architecture for agent memory, specifically how the assistant reasons about, writes, retrieves, updates, and retires memories across long-term home searches. You will drive context engineering by assembling and compressing information from conversation history, user memory, tools, and skills to ensure relevant, cost-efficient responses. Key responsibilities include building and orchestrating agents end-to-end, designing offline and online evaluation frameworks for memory quality, and leading cross-functional initiatives. The role requires expertise in Python and agentic AI frameworks like LangGraph, Agents SDK, or AutoGen. You will solve technical problems related to long-context techniques, self-evolving agentic systems, and maintaining personalized user insights within a production environment.

What does a Machine Learning Engineer earn in Remote?

Median $246638 from 41 postings across 11 companies.

See salary data

What you'll do

  • Shape the architecture for agent memory, including how the assistant reasons about, writes, retrieves, and retires memories.
  • Drive context engineering by assembling, prioritizing, and compressing context from conversation history, user memory, tools, and skills.
  • Build and orchestrate agents end-to-end, from prompt and context design through deployment and production operations.
  • Design and develop offline and online evaluation frameworks for memory and context quality to guide technical decisions.
  • Translate emerging agentic paradigms, such as long-context techniques and self-evolving systems, into tangible product innovations.
  • Lead complex, multi-team initiatives and communicate technical direction clearly across Engineering, partner teams, and leadership.

What we're looking for

  • 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.
  • Experience building and shipping LLM-based agents in production.
  • Hands-on experience building agents end-to-end, including orchestration, prompt engineering, and context engineering.
  • Experience evaluating agentic systems and using results to improve them.
  • Proven technical leadership experience influencing technical direction across teams and mentoring other engineers.
  • 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 (preferred).

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