Senior Applied Scientist, Media

Senior Applied Scientist, Rich Media Experiences page is loaded## Senior Applied Scientist, Rich Media Experiencesremote type:
Remote locations:
Remote-USAtime type:
Full time posted on:
Posted Todayjob requisition :
P748027## About the team

The Zillow Rich Media (RMX) team is transforming how people experience virtual home tours by building immersive, next-generation features that leverage mobile devices, machine learning, and computer vision. We collaborate across product, research, and engineering to develop innovative ways to capture, process, and present rich media, turning real-world signals into structured, interactive representations of homes within Zillow’s products.## About the role

As a Senior Applied Scientist, you will tackle complex, real-world challenges that directly shape Zillow’s virtual touring experiences. You’ll have a broad impact by defining and solving ambiguous problems, developing innovative models, and collaborating with cross-functional teams to deliver features that enhance how users explore homes. Your work will drive the next wave of immersive, user-centric experiences at Zillow.##
** You Will Get To
*** Frame and solve complex perception problems using scientific and engineering best practices.
* Collaborate with product, engineering, and design teams to translate user needs into research questions and solutions.
* Design, implement, and iterate on machine learning and computer vision models for structured understanding of spaces.
* Develop robust evaluation pipelines and experiments to measure and improve model performance.
* Integrate models into production systems, ensuring reliability and scalability.
* Monitor and improve deployed models based on real-world data and user feedback.
* Mentor and support team members in modeling, evaluation, and research practices.
* Communicate findings and technical decisions clearly to both technical and non-technical partners.

This role has been categorized as a Remote position. “Remote” employees do not have a permanent corporate office workplace and, instead, work from a physical location of their choice, which must be identified to the Company. U.S. employees may live in any of the 50 United States, with limited  California, Connecticut, Maryland, Massachusetts, New Jersey, New York, Washington state, and Washington DC the standard base pay range for this role is $ - $ annually.

This base pay range is specific to these locations and may not be applicable to other  Colorado, Hawaii, Illinois, Minnesota, Nevada, Ohio, Rhode Island, and Vermont the standard base pay range for this role is $ - $ annually. The base pay range is specific to these locations and may not be applicable to other  addition to a competitive base salary this position is also eligible for equity awards based on factors such as experience, performance and location.

Actual amounts will vary depending on experience, performance and location. Employees in this role will not be paid below the salary threshold for exempt employees in the state where they reside.## Who you are
* 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, Tensor Flow, or JAX), with a track record of building and deploying models.
* Experience shipping production ML systems, including data pipelines, deployment, monitoring, and iteration.
* Strong understanding of probability, statistics, and experimental design, with the ability to apply these to practical evaluation strategies.
* Demonstrated ability to work with noisy, imperfect datasets and design robust solutions for challenging edge cases.
* Experience with geometry-heavy or spatial understanding problems, or multi-modal/sensor-fusion challenges, is a plus.
* Proven ability to communicate complex technical ideas to both technical and non-technical audiences, and to collaborate effectively in cross-functional teams.
* Prior success in ambiguous, evolving problem spaces or zero-to-one environments is valued.
* Contributions to the broader ML or computer vision community (e.g., publications,…