Machine Learning Engineer
Remote-Germany
- Pay
- Pay not listed
- Work setting
Working pattern needs review — work setting source
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.
Listed location: Remote-Germany
Read the full posting- Employment
Full-time — employment source
Employment type in the employer’s listing: Full time
From the employer’s posting
What you’ll work on
Full postingThis is a high-impact individual contributor role for someone who loves operating at the intersection of modeling and systems.
Productionalization: Owning the transition from research code to production-ready and optimized models.
Turn research code into production-ready, optimized models
Build CI/CD pipelines so scientists can deploy models in short cycles
Design services that expose ML models to Zillow's customers
Own team datasets and prepare them for model training
Improve monitoring so scientists can track models in production
From the employer’s posting
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.
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
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.
Designing services to expose ML models to Zillow’s end customers
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.
Innovating upon our existing monitoring systems that make our services reliable and give scientists insight into the performance of their models in production.
What you’ll bring
All qualificationsCore experience
- You have 1-3 years professional experience building and shipping machine learning models or ML-powered systems in production.
- 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.
Preferred experience
- Experience in computer vision, spatial data, 3D, AR/VR, or related domains is a plus.
Qualification wording
You have 1-3 years professional experience building and shipping machine learning models or ML-powered systems in production.
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.
Experience in computer vision, spatial data, 3D, AR/VR, or related domains is a plus.
Tools in this posting
- Python
- TypeScript
- AWS
- Google Cloud (GCP)
- Kubernetes
- Spark
- Airflow
- PyTorch
- TensorFlow
Source — Tool mentions in context
- 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 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 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
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Jun 3, 2026 · 137 days ago
- Recorded sightings
- 240
- Last seen by us
- Oct 18, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
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Job description
About the team
As 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
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.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Remote-Germany
- 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.
- Work authorization
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.
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