Senior Machine Learning Engineer, Rich Media Experiences
Zillow · United States
- Hybrid
- Full-time
- $274,300 / year
- United States
Job highlights
- Build and operate production ML systems.
- Lead end-to-end ML lifecycle.
- Collaborate with science and engineering teams.
- Improve ML workflow reliability and performance.
- Mentor junior engineers and drive best practices.
About the role
About The Team
As a Senior Machine Learning Engineer within Zillow’s Rich Media Experiences team, you’ll join a group focused on helping people better understand homes through immersive, AI-powered experiences. The team works on turning photos, video, and spatial signals into structured representations that power customer-facing products used by millions of shoppers. Within Rich Media Experiences, the Instant Floor Plans team is building systems that transform sensor-rich mobile captures into accurate floor plans and 3D representations that feed Zillow’s rich-media and listing experiences.
About The Role
This is a high-impact senior individual contributor role for someone who loves operating at the intersection of modeling and systems. As a Senior Machine Learning Engineer, you’ll help shape how Zillow builds production-grade machine learning systems for rich media experiences, partnering across applied science and engineering to turn promising ideas into reliable, scalable product capabilities.
You Will Get To:
- Design, build, and operate production-grade machine learning systems that move from early ideas and prototypes into reliable customer-facing services.
- Lead end-to-end machine learning work spanning data, training, evaluation, deployment, observability, and iteration in production.
- Partner closely with applied scientists and software engineers across backend, web, and mobile to integrate modern machine learning techniques into Zillow experiences.
- Improve the quality, latency, reliability, and maintainability of machine learning workflows that support floor plan and rich media products.
- Drive technical decisions in ambiguous problem spaces, especially where structured inference, computer vision, spatial signals, or performance tradeoffs matter.
- Help establish shared patterns, tooling, and best practices that raise the bar for machine learning engineering across the team.
- Mentor peers through strong technical execution, code review, debugging discipline, and thoughtful communication across functions.
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 exceptions.
Who you are
- You have significant professional experience building and shipping machine learning models or ML-powered systems in production.
- You have strong hands-on proficiency in Python and at least one modern machine learning framework, such as PyTorch or TensorFlow.
- You have experience building and operating end-to-end machine learning workflows, including data pipelines, model training, evaluation, deployment, and monitoring.
- You have a strong foundation in machine learning fundamentals such as representation learning, structured prediction, computer vision, optimization, and failure analysis.
- You are comfortable debugging model and system behavior in real-world environments and using metrics, logs, and experiments to improve outcomes.
- You collaborate effectively with applied scientists, software engineers, and product partners in ambiguous, cross-functional settings.
- You have strong engineering judgment and know how to balance experimentation with reliability, speed, and long-term maintainability.
- You communicate technical ideas clearly and can influence decisions across disciplines.
- Experience in computer vision, spatial data, 3D, AR/VR, mapping, search, recommendation systems, or related domains is a plus.
About Zillow
At Zillow, we’re reimagining how people move—through the real estate market and through their careers. As the most-visited real estate platform in the U.S., we help customers navigate buying, selling, financing and renting with greater ease and confidence. Whether you're working in tech, sales, operations, or design, you’ll be part of a company that's reshaping an industry and helping more people make home a reality.
Zillow is honored to be recognized among the best workplaces in the country. Zillow was named one of FORTUNE 100 Best Companies to Work For® in 2025, and included on the PEOPLE Companies That Care® 2025 list, reflecting our commitment to creating an innovative, inclusive, and engaging culture where employees are empowered to grow.
No matter where you sit in the organization, your work will help drive innovation, support our customers, and move the industry—and your career—forward, together.
Equal Opportunity Employer
Zillow Group is an equal opportunity employer committed to fostering an inclusive, innovative environment with the best employees. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please contact your recruiter directly.
Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable state and local law.
Los Angeles County applicants
Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Key skills/competency
- Machine Learning Engineering
- Python
- PyTorch/TensorFlow
- Production ML Systems
- Computer Vision
- Spatial Data
- 3D Representations
- Data Pipelines
- Model Deployment
- ML Operations
Skills & topics
- Machine Learning Engineer
- Python
- PyTorch
- TensorFlow
- Machine Learning
- Computer Vision
- Data Science
- AI
- Software Engineering
- Production ML
- Spatial Data
- 3D Modeling
- Remote
- Zillow
How to get hired
- Tailor your resume: Highlight experience with Python, ML frameworks (PyTorch/TensorFlow), and production ML systems. Quantify achievements in building and deploying ML models.
- Showcase relevant projects: Emphasize experience in computer vision, spatial data, and 3D representations if applicable. Detail end-to-end ML workflow management.
- Prepare for technical interviews: Expect questions on ML fundamentals, structured prediction, and debugging real-world ML systems. Be ready to discuss system design and trade-offs.
- Understand Zillow's mission: Research Zillow's impact on the real estate market and their use of AI for rich media experiences. Align your contributions to their goals.
- Network and engage: Connect with Zillow recruiters or employees on LinkedIn to gain insights into the team and culture.
Technical preparation
Behavioral questions
Frequently asked questions
- What is the typical career path for a Senior Machine Learning Engineer at Zillow?
- At Zillow, a Senior Machine Learning Engineer on the Rich Media Experiences team often progresses by deepening their expertise in ML systems, potentially moving into Staff or Principal Engineer roles, or specializing further in areas like computer vision or spatial data. Leadership opportunities may also arise, guiding technical strategy for the team or contributing to broader ML initiatives across the company. Mentoring junior engineers is a key part of the role, fostering growth within the team.
- What are the key differences between this Senior Machine Learning Engineer role and other ML roles at Zillow?
- This Senior Machine Learning Engineer role is specifically focused on the Rich Media Experiences team, concentrating on transforming visual and spatial data (photos, video, sensor captures) into structured representations for products like Instant Floor Plans. This involves a strong emphasis on computer vision, spatial signals, and building production-grade ML systems from prototype to deployment, distinct from roles that might focus on, for example, search algorithms or financial modeling.
- How does Zillow support remote work for its Senior Machine Learning Engineers?
- Zillow supports remote work by allowing employees to work from a physical location of their choice within the U.S. (with limited exceptions). This means you'll have the flexibility to work from home, provided it's identified to the company. Collaboration and communication tools are in place to ensure seamless teamwork across distributed teams.
- What kind of impact can a Senior Machine Learning Engineer have at Zillow?
- As a Senior Machine Learning Engineer, you'll have a significant impact by designing and operating production ML systems that directly enhance Zillow's customer-facing products. Your work on turning raw media into structured data powers experiences used by millions, contributing to Zillow's mission of reimagining how people move.
- What are Zillow's expectations for a Senior Machine Learning Engineer in terms of technical skills?
- Zillow expects Senior Machine Learning Engineers to have significant professional experience building and shipping ML models/systems in production. Key technical skills include strong proficiency in Python, expertise in ML frameworks like PyTorch or TensorFlow, and a solid understanding of ML fundamentals (representation learning, structured prediction, computer vision). Experience with end-to-end ML workflows, including deployment and monitoring, is crucial.
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