AI Applied Scientist – PhD Intern, Next-Gen Agentic and Multi-Modal Home Exploration Experience

October 3

🏄 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

💵 $104k - $166k / year

👨‍🎓 Internship

⚪️ Entry-level

🧬 Research Scientist

🦅 H1B Visa Sponsor

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Zillow

WebsiteLinkedInAll Job Openings

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

• As an intern, you will use your expertise in Agentic systems, conversational AI, LLMs, and multi-modal inference to advance customer-facing experiences and interfaces. • Your research will help build AI agents capable of handling complex, rich media oriented, multi-turn interactions while maintaining context and taking appropriate actions. • Your internship will develop the next-generation real estate shopping experience that integrates Agentic and Multi-modal reasoning to transform how users find their ideal homes through pushing research problems including but not limited to: • Personalized and Guided Home Exploration: An agentic approach that proactively guides and helps users navigate millions of listings to identify the best homes, the experience should be highly engaging, fun and goal oriented. • Conversational Optimization: Enhanced multi-turn conversations with effective context management and improved dialogue quality, achieved through organized data from retrieved results. • Multi-modal Collaboration System: A combination of 3D computer vision (utilizing 3D reconstructions and Gaussian splats) and LLM interfaces, powered by conversational AI.

🎯 Requirements

• Currently enrolled in a PhD program in computer science, NLP, machine learning, or a related field, with solid publication record • Background in at least one of the following areas: Human computer interaction (HCI) • User behavior research in the context of agentic AI • Agentic AI (tool use, planning, reasoning, decision-making) • Conversational AI and dialogue optimization • Multi-modal inference models with focus on combining 3D Computer Vision and LLMs • Multi-agent systems and orchestration • Memory systems and context engineering • Reinforcement learning and reward modeling • Familiarity with modern deep learning frameworks (e.g., PyTorch, Hugging Face Transformers) • Strong research mindset, with motivation to publish • Interest in applying AI to complex, multi-stakeholder domains

🏖️ Benefits

• comprehensive medical, dental, vision, life, and disability coverages • parental leave • family benefits • retirement contributions • paid time off