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As the engine behind Zillow Group's mission to build a seamless digital real estate marketplace, the Shopping AI team is fundamentally redefining how millions of people discover and shop for homes. Our team of engineers and scientists builds and owns the production machine learning systems that power Zillow's core user experience, including personalized ranking & recommendations, semantic search, autocomplete, and display optimization. Working closely with product and design, we apply the latest advancements in AI to solve unique, large-scale challenges. As we look forward, we are tackling the next generation of questions, including how generative AI can unlock intuitive, personalized experiences for every home shopper.
Job Responsibility
Design, build, and ship production new machine learning models that power core product features on the Zillow app, website, and email/push notifications
Re-architect our core home ranking and recommendation systems to support advanced neural networks and dramatically accelerate the pace of experimentation across surfaces
Own the full lifecycle of your models, from offline experimentation and prototyping with massive datasets to online deployment, A/B testing, and performance monitoring
Pioneer the application of cutting-edge deep learning and large language models (LLMs) to improve our home shopping experience
Develop new AI components that optimize how we display and when we recommend homes, ensuring we connect shoppers with the right content on the right properties at the right time
Collaborate in a cross-functional group of engineers, applied scientists, product managers, and designers to define, execute, and iterate on the team's strategic roadmap
Contribute to the team's engineering excellence by improving our machine learning infrastructure, development standards, and shared tooling
Act as a key technical voice, mentoring other engineers and helping to shape the long-term vision for artificial intelligence in the home shopping experience
Requirements
3-5 years of experience in developing applications in search, personalized ranking, or recommender systems
Experience developing and deploying ML models that scale to high-traffic, latency sensitive customer-facing services (100s of millions of requests per day)
Strong programming skills in a high-level language such as Python or Java
Familiarity with common machine learning libraries like PyTorch, TensorFlow, Catboost, scikit-learn and huggingface (repository)
Expertise with large scale distributed data processing systems such as Hive, Spark, Airflow, or Databricks
Experience owning the full lifecycle of customer facing machine learning models, from offline experimentation and prototyping to online deployment, A/B testing, and performance monitoring
Nice to have
A Master's degree + 3 yrs or BS with a minimum of 5 yrs of experience (preferably in large consumer tech companies)
Prior experience or high level of curiosity with generative AI and excitement to collaborate on what they’ve learned!