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Staff Machine Learning Engineer

3 months ago

Austin, Texas, United States Realtor Full time

At , we have among the most comprehensive and accurate coverage of real estate listings and the most engaged users across all the online real estate portals. Our mission is to make buying, selling, renting, and living in homes easier and more rewarding for everyone.
Building your career? Build it better at . Join us and help change the world of real estate, one home at a time.
Staff Machine Learning Engineer at (View all jobs)
Location : Austin, TX
At , we process terabytes of data every day and transform that data into information that powers decisions for millions of home buyers, renters, dreamers, and real estate professionals. Our mission is to make buying, selling, renting, and living in homes easier and more rewarding for everyone.
We seek an experienced Staff Machine Learning Engineer - MLOps Platform to join our Machine Learning team and help take it to the next level. As a key member of the team, you will be responsible for the shared core infrastructure that serves as the foundation for our algorithms. You will drive enhancements and maintenance of our Paved Path development process as well as play a role in optimizing and tuning model performance.
What you'll do:

  • Design the data pipelines and engineering infrastructure to support our machine learning systems at scale and in near-real time
  • Identify and evaluate new technologies to improve the performance, maintainability, and reliability of our machine learning systems
  • Build CI/CD pipelines orchestration by GitLab CI, GitHub Actions, Circle CI, Airflow or similar tools
  • Apply software engineering rigor and best practices to machine learning, including CI/CD, automation, testing, etc.
  • Support model development, with an emphasis on audibility, versioning, and data security
  • Effectively partner with product and other engineering teams

How we work:
We balance creativity and innovation on a foundation of in-person collaboration. For most roles, our employees work three or more days in our offices, where they have the opportunity to collaborate in person, adding richness to our culture and knitting us closer together.
What you'll bring:

  • PhD/MS in computer science, statistics, mathematics, operations research, or related fields and 4 years of relevant experience, or BS/MS degree and 7+ years of experience
  • Experienced in Python, R, Spark, or other languages and frameworks appropriate for large-scale analysis of structured and unstructured data.
  • Working experience with relational databases (SQL) and large-scale distributed systems.
  • Ability to design and implement cloud solutions (AWS preferred)
  • Experience building custom integrations between cloud-based systems using APIs
  • Experience with MLOps Frameworks like Kubeflow, MLFlow, DataRobot, Airflow, etc.,
  • Experience developing with containers and Kubernetes in cloud computing environments
  • Strong understanding of software testing, benchmarking, and continuous integration
  • Exposure to machine learning methodology and best practices
  • Exposure to deep learning approaches and modeling frameworks (PyTorch, Tensorflow, Keras, etc.)

Do the best work of your life at
Here, you'll partner with a diverse team of experts as you use leading-edge tech to empower everyone to meet a crucial goal: finding their way home. And you'll find your way home too. People are our foundation-the core that drives us passionately forward. At , you'll bring your full self to work as you innovate with speed, serve our consumers, and champion your teammates. In return we'll provide you with a warm, welcoming, and inclusive culture; intellectual challenges; and the development opportunities you need to grow.
Diversity is important to us, therefore, is an Equal Opportunity Employer regardless of age, color, national origin, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, marital status, status as a disabled veteran and/or veteran of the Vietnam Era or any other characteristic protected by federal, state or local law. In addition, will provide reasonable accommodations for otherwise qualified disabled individuals.