Machine Learning Engineer

Posted 7 Days Ago
Be an Early Applicant
Hiring Remotely in Germany
Remote
45K-70K Annually
Junior
Other • Real Estate • PropTech
The Role
As a Machine Learning Engineer, you'll build production-grade ML systems, define CI/CD pipelines, manage datasets, and collaborate with scientists on model training.
Summary Generated by Built In

About the teamAs a Machine Learning Engineer within Zillow’s Rich Media Virtual Staging AI 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, the VSAI team is building systems that transform home media into products that enrich the understanding of a home.

About the role

This is a high-impact individual contributor role for someone who loves operating at the intersection of modeling and systems. As a 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:
  • Productionalization: Owning the transition from research code to production-ready and optimized models. Establishing CI/CD pipelines that allow scientists to deploy models in short iteration cycles. Innovating upon our existing monitoring systems that make our services reliable and give scientists insight into the performance of their models in production. Designing services to expose ML models to Zillow’s end customers

  • Data: Good data is key to many SOTA ML methods. You will own our team’s datasets, lead and support data engineering projects, understand datasets from other teams, and collaborate with scientists and other teams to prepare them for model training.

  • Training & Experimentation: Owning projects and supporting scientists in running large-scale training and data processing by collaborating with them on specific projects, establishing generalized best practices, and sharing expertise around performance and software engineering principles, while leveraging AI coding and productivity tools.

  • Modeling: Staying on top of cutting-edge research (for example, on platforms like Arxiv, X, and Papers With Code) and modifying its methods for our use cases in innovative ways to enable new product experiences or improve existing ones.

  • Dev & MLOps: Establishing best practices around code quality, testing, and ownership that allow us to move fast without compromising reliability (and sleep). Participating in our existing on-call rotation

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 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 1-3 years 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, JAX or TensorFlow.

  • You have hands-on experience with cloud platforms (AWS, GCP) and container orchestration (Kubernetes)

  • You have experience with data engineering tools and building robust data pipelines (e.g., Spark, Airflow, streaming systems)

  • You have experience using backend code languages such as TypeScript or Go to fully implement ML-powered systems end-to-end

  • 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.

Nice to have 

  • Experience in computer vision, spatial data, 3D, AR/VR, or related domains is a plus.

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 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.

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.

Skills Required

  • 1-3 years professional experience building ML models
  • Strong proficiency in Python
  • Experience with ML frameworks (e.g., PyTorch, JAX, TensorFlow)
  • Hands-on experience with AWS or GCP
  • Experience with Kubernetes
  • Experience with data engineering tools (e.g., Spark, Airflow)
  • Experience with backend languages (TypeScript or Go)
  • Strong foundation in machine learning fundamentals

Zillow Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Zillow and has not been reviewed or approved by Zillow.

  • Healthcare Strength Healthcare coverage is described as comprehensive, spanning medical, dental, vision, and robust mental-health resources with coaching and app-based support. Wellness reimbursements and wellbeing tools reinforce a strong emphasis on overall health.
  • Parental & Family Support Parental benefits are noted as fully paid and expansive, including bonding leave, ramp-back options, and a new-baby stipend. Additional family-forming support such as fertility coverage, adoption/surrogacy assistance, breast milk shipping, and backup childcare deepens this strength.
  • Flexible Benefits A distributed-first work model offers broad location flexibility, with home-office support and short-term international work options. This flexibility pairs with generous PTO, holidays, sick leave, and a sabbatical program as key parts of the total package.

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The Company
HQ: Seattle, WA
7,863 Employees
Year Founded: 2006

What We Do

Join our mission to give the people power to unlock life’s next chapter. Our homes are the heartbeat of our lives, and we believe that finding a home shouldn’t be so hard in today’s always-on world. That’s why we’re reimagining the traditional rules of real estate to make it easier than ever to move from one home to the next. Our journey began nearly 15 years ago with a handful of employees and one big idea: to make it radically easier for people to move. We began by helping people understand and track their homes with the Zestimate, our proprietary algorithm, and then with advanced technology and valuable connections with real estate professionals. Today, Zillow has become a household name. People are more likely to search for “Zillow” than “real estate,” and our name is often used as a verb. While other industries have ushered in a new era of convenience, the time for seamless and convenient real estate experience is now. This is our next chapter as a company. We’re looking for smart, passionate adventurers to join us as we reimagine the real estate transaction and change the way people buy, sell, rent and finance their homes.

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