Jobs Companies Zillow Senior Machine Learning Engineer, Rich Media Experiences

Sobre este puesto de Senior Machine Learning Engineer, Rich Media Experiences en Zillow

Zillow · Remoto · Remote-USA

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.

In California, Connecticut, Maryland, Massachusetts, New Jersey, New York, Washington state, and Washington DC the standard base pay range for this role is $171,700.00 - $274,300.00 annually. This base pay range is specific to these locations and may not be applicable to other locations. In Colorado, Hawaii, Illinois, Maine, Minnesota, Nevada, Ohio, Rhode Island, Vermont, and Virginia the standard base pay range for this role is $163,200.00 - $260,600.00 annually. The base pay range is specific to these locations and may not be applicable to other locations.

In 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

  • 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.


Here at Zillow, we value the experience and perspective of candidates with non-traditional backgrounds. We encourage you to apply if you have transferable skills or related experiences.

Get to know us

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 people 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 reshaping an industry and helping more people make home a reality.


How we work is a key part of that transformation. Through Cloud HQ, our strategic approach to distributed work, most employees have the flexibility to work from wherever they’re most productive—enabling us to move fast, stay connected and deliver on our people promise. 


Zillow is honored to be recognized among the best workplaces in the U.S. Zillow was named one of FORTUNE 100 Best Companies to Work For® in 2026, and included on TIME’s America’s Best Companies 2026 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.


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, age, citizenship, marital status, 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.

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Cómo se compara este salario de ML Engineer

Este puesto paga $211,900/yren línea con el rango típico para los puestos de ML Engineer.

$128,304 la mediana de $201,700 $293,996

Rango típico $165,000–$250,000/yr, a partir de 1,105 ofertas comparables de ML Engineer en JobsRadar (salario anualizado en USD). Ver datos salariales de ML Engineer →

Sobre Zillow

At Zillow, flexibility isn’t a perk - it’s how we work. Cloud HQ is our distributed work model, built on trust, clear systems, and the belief that you can do great work from wherever you are. It’s not about where you work. It’s about moving forward - together.

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