Principal Machine Learning Engineer, Memory & Context

🔥 13 hours ago

🇺🇸 United States – Remote

💵 $199k - $334.6k / year

⏰ Full Time

🔴 Lead

🤖 Machine Learning Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

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Zillow

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 2006

🏠 Real Estate

🛍️ eCommerce

👥 B2C

💰 $4.1M Post-IPO Equity on 2012-12

Real Estate • eCommerce • B2C

Zillow is a leading real estate and property rental marketplace that provides comprehensive information on homes, apartments, and properties for sale or rent. It offers users tools to search for properties, calculate mortgage rates, and connect with real estate agents. The platform also features innovative algorithms that provide Zestimates, which are estimated market values of homes. Zillow is a go-to resource for individuals looking to buy, sell, or rent properties, as well as for agents and brokers who want to reach a wider audience.

📋 Description

• Own the architecture of agent memory, including what the assistant remembers and how memories are written, retrieved, updated, and retired • Lead context engineering for production agents by assembling, prioritizing, and compressing context • Build and orchestrate agents end to end, from prompt and context design to deployment and production operation • Define offline and online evaluation frameworks for memory and context quality • Use evaluation results to drive product and technical decisions • Track emerging agentic paradigms, memory architectures, and long-context techniques and convert them into product innovation • Lead complex, multi-team initiatives • Communicate technical direction to engineers, partner teams, and leadership

🎯 Requirements

• 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 and experience influencing technical direction across teams and mentoring other engineers • Strong communication skills, including presenting to senior leadership • Strong programming skills in Python • Familiarity with agentic AI frameworks such as LangGraph, Agents SDK, or AutoGen • Employees must reside in one of the 50 United States, with limited exceptions

🏖️ Benefits

• Equity awards based on factors such as experience, performance and location • Remote work from a physical location of choice • Flexible work from wherever employees are most productive • Equal employment opportunity and inclusive, innovative environment • Disability or special-needs accommodation