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Zillow is a leading online real estate marketplace covering the whole spectrum of purchasing, owning, and selling a home. In support of flexible work options an
Senior Machine Learning Engineer, Shopping AI
Location
California + 7 moreAll locations: California | Connecticut | District of Columbia | New Jersey | New York | Maryland | Massachusetts | Washington
Posted
122 days ago
Salary
$171.7K - $274.3K / year
Seniority
Senior
Job Description
Senior Machine Learning Engineer, Shopping AI
Zillow
• 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.
Job 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
Benefits
- equity awards based on factors such as experience, performance and location
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