Zillow's AI Org needs to deliver unique AI-powered experiences for hundreds of millions of customers by connecting buyers with the right professionals to help realize their home-buying dreams.
Requirements
- Proficiency with a high-level programming language (we most commonly use Python)
- Practical knowledge of statistics (for example, causal inference, Frequentist or Bayesian inference)
- Experience prototyping, developing, and implementing algorithmic solutions and new technologies with diverse analytics and data.
- Hands-on experience in deploying machine learning models into realtime production environments.
- Experience working with large scale datasets and building ETL pipelines using Spark, Kubeflow, and DataBricks.
- Strong understanding of Machine Learning and Natural Language Processing fundamentals.
- Experience with Machine Learning tools and Frameworks (e.g. PyTorch, Transformers, XGBoost, scikit-learn, etc.)
Responsibilities
- Apply a growth-mindset and first principles to ambiguous customer problems to rapidly iterate on novel solutions and ways of working.
- Collaborate closely with applied scientists, engineering, design and research to understand, scope, design, prototype, implement and iterate on internal and external facing systems supporting and implementing next generation AI applications.
- Shepherd the deployment of machine learning applications into production with an eye towards reliability.
- Cultivate connections with other teams for critical dependencies and infrastructure.
- Contribute to carrying and growing our team culture of rapid innovation and creative frugality.
Other
- The communication skills to influence, collaborate with, and educate others (whom you may need to educate on methods and requirements in experimentation and statistics).
- The tenacity to embrace and tackle challenging problems.
- Practiced technical ability and passion for both owning implementation and contributing technical/thought leadership for a team of world-class scientists engineers.
- Experience with generative AI or large language models and related technologies (knowledge retrieval solutions, for example).
- Experience with regulated, private or sensitive data, document understanding, user interest modeling, or reinforcement learning.
