Applied Scientist – New Construction

Job not on LinkedIn

🕒 February 10

🏄 California, Colorado, +14 more states – Remote

🏄 California – Remote ⛰️ Colorado – Remote 🦌 Connecticut – Remote 🏛️ District of Columbia – Remote 🌺 Hawaii – Remote 🌽 Illinois – Remote 🎰 Nevada – Remote 🏖️ New Jersey – Remote 🗽 New York – Remote 🏈 Ohio – Remote 🦀 Maryland – Remote 🍂 Massachusetts – Remote ❄️ Minnesota – Remote ⚓ Rhode Island – Remote 🍁 Vermont – Remote ☕ Washington – Remote

💵 $136.3k - $217.7k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🧬 Research Scientist

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 35%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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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

• Research, design, and prototype new machine learning models for Zillow’s consumer products, including search, ranking, recommendations, and notifications. • Lead the full model lifecycle: from ideation and offline experimentation on large datasets to online deployment, A/B testing, and ongoing performance monitoring. • Develop and test novel modeling approaches, such as deep learning architectures and large language models (LLMs), to improve the home-shopping experience. • Apply cutting-edge AI techniques, including LLM-based retrieval and RAG-style systems, to create more natural and conversational property search experiences. • Optimize how and when homes are displayed to users, ensuring relevance and context in every interaction. • Collaborate with engineers, product managers, and designers to define, execute, and iterate on impactful projects. • Partner with data engineering and infrastructure teams to leverage large-scale distributed data systems for feature engineering and model training.

🎯 Requirements

• Experienced in designing, training, and analyzing machine learning models to solve real-world business problems, not just academic benchmarks. • Proficient in Python and familiar with common ML libraries (e.g., PyTorch, TensorFlow, CatBoost, scikit-learn, Hugging Face) and distributed data systems (e.g., Spark, Hive, Databricks, Airflow). • Skilled in the scientific lifecycle: hypothesis formation, experiment design, result analysis, and clear communication to technical and non-technical partners. • Demonstrated experience in at least one of the following: search/information retrieval, personalized ranking/recommender systems, or generative AI/LLM-based systems. • Holds a PhD or Master’s degree in a relevant field (Computer Science, AI, Data Science, or related), or equivalent industry experience (typically 3-4+ years with a Master’s, or 1+ year with a PhD). • Comfortable working near production systems and collaborating closely with engineers and cross-functional partners. • Brings curiosity and excitement for applying generative AI and LLMs to transform the home-shopping experience. • Approaches challenges with ownership, scientific rigor, and a growth mindset.

🏖️ Benefits

• In addition to a competitive base salary this position is also eligible for equity awards based on factors such as experience, performance and location. • Employees in this role will not be paid below the salary threshold for exempt employees in the state where they reside.