Sr Machine Learning Engineer, Search

Austin, Texas, United States

Recognized as the No. 1 site trusted by real estate professionals, Realtor.com® has been at the forefront of online real estate for over 25 years, connecting buyers, sellers, and renters with trusted insights and expert guidance to find their perfect home. Through its robust suite of tools, Realtor.com® not only makes a significant impact on the real estate industry at large, but for consumers, navigating the biggest purchase they will make in their life, by providing a user experience that is easy to use, easy to understand, and most of all, easy to make decisions.

Join us on our mission to empower more people to find their way home by breaking barriers to entry, making the right connections, and building confidence through expert guidance.

At Realtor.com, we’re on a mission to revolutionize the way people find and secure their dream homes. Every day, we process terabytes of data to power intelligent search and personalized recommendations that serve millions of home buyers, renters, and real estate professionals. Our core search engine sits at the heart of this experience—helping users discover the right home faster, with greater confidence.

We’re looking for a Senior Machine Learning Engineer to help redefine how search works in real estate. You’ll play a key role in shaping the intelligence behind our search ranking and relevance models, leveraging state-of-the-art machine learning techniques to improve how users interact with our platform. If you’re passionate about applied AI, big data, and building cutting-edge ML solutions that have real-world impact, we’d love to hear from you!

Three Reasons to Apply:

  • Opportunity to transform real estate search using cutting-edge ML techniques
  • Work on high-impact projects serving millions of users daily
  • Collaborate across teams to shape innovative search-driven experiences

What You’ll Do:

  • Transform Search with ML – Design, build, and optimize machine learning models that power our core search ranking and relevance systems, ensuring users find the most relevant listings effortlessly.
  • Enhance Personalization – Develop advanced recommendation algorithms to tailor search results based on user behavior, preferences, and intent.
  • Build Data Pipelines at Scale – Create and optimize ETL pipelines to process massive datasets, making real-time search intelligence possible.
  • Leverage the Latest in AI – Apply state-of-the-art techniques in NLP, deep learning, and reinforcement learning to enhance search relevance, query understanding, and ranking.
  • Deploy & Optimize in Production – Take ML models from experimentation to production using AWS, Docker, and scalable distributed systems.
  • Collaborate Across Teams – Work closely with engineering, product, and data science teams to define new search-driven experiences and ensure seamless deployment of ML solutions.

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:

  • Expertise in ML & Search – PhD/MS in computer science, statistics, mathematics, operations research or related fields and 2 years of relevant experience in data science, machine learning or applied statistics, with a strong background in information retrieval, search ranking, recommendation systems, or related ML applications.
  • Extensive Technical Skills – Proficiency in Python, Spark, TensorFlow/PyTorch, and SQL. Experience with large-scale distributed systems is a plus.
  • Production ML Experience – Hands-on experience deploying ML models at scale using cloud platforms like AWS, Kubernetes, or similar.
  • Strong Creative Thinking & Problem-Solving Skills – Passion for tackling complex search and ranking challenges, improving user experience, and driving measurable impact.
  • Excellent Communication – Ability to articulate ML concepts to both technical and non-technical stakeholders.

How We Reward You:

Realtor.com® is committed to investing in the health and wellbeing of our employees and their families. Our benefits programs include, but are not limited to:

  • Inclusive and competitive medical, Rx, dental, and vision coverage.
  • Family-forming benefits.
  • 13 Paid Holidays.
  • Flexible Time Off.
  • 8 hours of paid Volunteer Time Off.
  • Immediate eligibility into Company 401(k) plan with 3.5% company match.
  • Tuition Reimbursement program for degreed and non-degreed programs.
  • 1:1 personalized Financial Planning Sessions.
  • Student Debt Retirement Savings Match program.
  • Free snacks and refreshments in each office location.

This is your opportunity to make a tangible impact on how millions of people discover and purchase homes. If you’re excited about building world-class search experiences powered by AI, join us and shape the future of real estate search!

Do the best work of your life at Realtor.com®

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 Realtor.com®, 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, Realtor.com® 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, Realtor.com® will provide reasonable accommodations for otherwise qualified disabled individuals.

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