Realtor.com is looking to redefine how search works in real estate by improving search ranking and relevance models using state-of-the-art machine learning techniques to enhance user interaction with their platform.
Requirements
- 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.
- Proficiency in Python, Spark, TensorFlow/PyTorch, and SQL.
- Experience with large-scale distributed systems is a plus.
- 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.
Responsibilities
- Design, build, and optimize machine learning models that power our core search ranking and relevance systems, ensuring users find the most relevant listings effortlessly.
- Develop advanced recommendation algorithms to tailor search results based on user behavior, preferences, and intent.
- Create and optimize ETL pipelines to process massive datasets, making real-time search intelligence possible.
- Apply state-of-the-art techniques in NLP, deep learning, and reinforcement learning to enhance search relevance, query understanding, and ranking.
- Take ML models from experimentation to production using AWS, Docker, and scalable distributed systems.
- Work closely with engineering, product, and data science teams to define new search-driven experiences and ensure seamless deployment of ML solutions.
Other
- 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
- 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.
