Senior Applied Scientist, Rich Media Experiences

Zillow Zillow · Consumer · United States · Remote

Senior Applied Scientist role focused on developing and deploying machine learning and computer vision models for Zillow's rich media experiences, specifically for virtual home tours. The role involves framing and solving perception problems, building and iterating on models, developing evaluation pipelines, integrating models into production, and mentoring team members. Experience with real-world data, Python, deep learning frameworks, and shipping production ML systems is required.

What you'd actually do

  1. Frame and solve complex perception problems using scientific and engineering best practices.
  2. Collaborate with product, engineering, and design teams to translate user needs into research questions and solutions.
  3. Design, implement, and iterate on machine learning and computer vision models for structured understanding of spaces.
  4. Develop robust evaluation pipelines and experiments to measure and improve model performance.
  5. Integrate models into production systems, ensuring reliability and scalability.

Skills

Required

  • Machine Learning
  • Computer Vision
  • Python
  • Deep Learning Frameworks (PyTorch, TensorFlow, JAX)
  • Production ML Systems
  • Data Pipelines
  • Model Deployment
  • Model Monitoring
  • Model Iteration
  • Probability
  • Statistics
  • Experimental Design
  • Evaluation Strategies
  • Noisy Datasets
  • Challenging Edge Cases
  • Communication
  • Cross-functional Collaboration

Nice to have

  • Geometry-heavy or spatial understanding problems
  • Multi-modal/sensor-fusion challenges
  • Ambiguous problem spaces
  • Zero-to-one environments
  • Publications
  • Patents
  • Open-source contributions

What the JD emphasized

  • 5+ years of experience as an applied or research scientist working on machine learning or computer vision with real-world data.
  • Proficiency in Python and at least one deep learning framework (e.g., PyTorch, TensorFlow, or JAX), with a track record of building and deploying models.
  • Experience shipping production ML systems, including data pipelines, deployment, monitoring, and iteration.

Other signals

  • machine learning
  • computer vision
  • production ML systems
  • structured understanding of spaces