Zillow is looking to advance intelligent systems that empower millions of customers for their home shopping journey by building cutting-edge models and agentic workflows that can provide actionable recommendations and execute tasks on behalf of users during one of the most complex and high-stakes financial decisions of their lives.
Requirements
- Advanced research in natural language processing (NLP) and/or reinforcement learning (RL)
- Practical experience fine-tuning and adapting large language models (LLMs) for specific use cases
- Familiarity with the design and implementation of automated/ agentic workflows
- Deep understanding of LLMs, hands on experience of post-training with the most popular OSS models
- Proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow)
Responsibilities
- Researching and developing techniques for fine-tuning LLMs with domain-specific data
- Applying reinforcement learning to optimize model performance for user-centric outcome
- Designing and prototyping agentic workflows that can autonomously perform tasks and assist home buyers
- Collaborating with cross-functional teams to evaluate and deploy research prototypes
- Sharing insights through presentations, documentation, and potentially publications
Other
- Currently enrolled in a PhD program in Computer Science, Machine Learning, Artificial Intelligence, or a related field with a strong publication record
- Excited about applying advanced AI methods to impactful, real-world problems
- Strong communication skills and ability to work collaboratively in a multidisciplinary environment
- Strong research mindset, with motivation to publish
- This role has been categorized as a Remote position.
