Machine Learning Engineer – User Understanding

7 hours ago

🏄 California – Remote

Although this job is listed in California, this company may be open to hiring remote in other states.

🦌 Connecticut – Remote

Although this job is listed in Connecticut, this company may be open to hiring remote in other states.

+6 more states

🏄 California – Remote 🦌 Connecticut – Remote 🏖️ New Jersey – Remote 🗽 New York – Remote 🦀 Maryland – Remote 🍂 Massachusetts – Remote ☕ Washington – Remote

💵 $145.5k - $232.5k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

🦅 H1B Visa Sponsor

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Zillow

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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.

5001 - 10000 employees

Founded 2006

🏠 Real Estate

🛍️ eCommerce

👥 B2C

💰 $4.1M Post-IPO Equity on 2012-12

📋 Description

• Build and maintain data pipelines for LLM (Large Language Model) training and evaluation, curate user-understanding signals (such as intents, preferences, and behavioral features), and ensure data quality, privacy, and proper dataset management. • Develop and manage labeling and feedback loops, including heuristics, annotation jobs, and prompt-based labeling, to create high-quality corpora, collaborating with Data Engineering and Applied Science partners to improve data coverage and reduce noise. • Design, prototype, and ship to production agentic AI solutions, including multi-agent systems using frameworks like LangGraph, and implement context-aware features in partnership with senior engineers. • Implement an evaluation framework to measure model quality on offline test sets (accuracy, bias, safety, user-intent coverage), and build dashboards to track improvements over time. • Lead and contribute to experimentation by implementing metrics, A/B tests, and monitoring, helping to harden prototypes for reliable rollouts. • Collaborate with senior engineers and cross-functional partners to select the right technologies, participate in code reviews, and share best practices (including mentoring interns or new hires as needed). • Summarize research findings and model evaluations into clear write-ups and demos for the team and cross-functional stakeholders.

🎯 Requirements

• A master’s degree or above, or equivalent experience in Computer Science, Electrical Engineering, or a related field, with an emphasis on building products using frontier multimodal LLMs (Large Language Models). • Expertise in agentic AI, pretraining, fine-tuning, and reinforcement learning of large language models. • 3+ years of hands-on experience building large-scale, high-impact solutions, ideally with recent experience in agent-based systems, multi-agent collaboration, or similar paradigms. • Experience deploying and scaling AI services capable of handling hundreds of millions of daily interactions with high availability, low latency, and robust fault tolerance. • A track record of writing articles and publishing high-impact research in top AI conferences is a big plus.

🏖️ Benefits

• competitive base salary • equity awards based on experience, performance, and location