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Zillow

Reimagining real estate to make it easier than ever to move from one home to the next.

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

Research ScientistResearch ScientistInternshipRemoteEntry LevelTeam 5,001-10,000Since 2006H1B SponsorCompany SiteLinkedIn

Location

California + 7 moreAll locations: California, Connecticut, District of Columbia, New Jersey, New York, Maryland, Massachusetts, Washington

Posted

167 days ago

Salary

$104K - $166K / year

Seniority

Entry Level

Postgraduate DegreeEnglishPyTorch

Job 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.

Job 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

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