Role overview
- 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.
- Proficiency with a high-level programming language (we most commonly use Python)
- Practical knowledge of statistics (for example, causal inference, Frequentist or Bayesian inference)
- The communication skills to influence, collaborate with, and educate others (whom you may need to educate on methods and requirements in experimentation and statistics).
- 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.)
- 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.
- Bachelor's degree or equivalent experience in Computer Science, or a related field.
Preferred qualifications
- 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.
- Experience collaborating with science, engineering, design, research and product partners in a team with a startup culture.
- Advanced degree (M.S. or Ph. D.) or equivalent experience in Computer Science or Engineering, Machine Learning, or related field.
About the company
At Zillow, our mission is to give people the power to unlock life’s next chapter. Zillow’s AI Org plays an important part in delivering unique AI-powered experiences for the hundreds of millions of customers who visit Zillow websites each month.
The Connections AI team iterates quickly and solves problems at the forefront of AI product development. This role requires an entrepreneurial approach and a driven curiosity about the constantly evolving field of ML Modeling, LLMs and AI-powered assistants.
As a Machine Learning Engineer (MLE) on the Connections AI team, you’ll be a part of a skilled group of applied scientists, software developers, and other machine learning engineers working together to connect buyers with the right professionals to help realize their home-buying dreams.