Realtor.com® is looking to solve the problem of empowering more people to find their way home by breaking barriers to entry, making the right connections, and building confidence through expert guidance in the real estate industry.
Requirements
- Expertise in Applied ML – 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, forecasting, recommendation systems, or related ML applications. Experience with causal ML is a plus.
- Production ML Experience – Hands-on experience deploying ML models at scale using cloud platforms like AWS, Kubernetes, or similar.
- Extensive Technical Skills – Proficiency in Python, Spark, TensorFlow/PyTorch, and SQL.
- Experience with large-scale distributed systems is a plus.
Responsibilities
- Own the full ML lifecycle: from data exploration to model development, deployment, and continuous optimization.
- Develop scalable, production-ready ML models that power key business initiatives, including monetization, pricing optimization, and intelligent recommendations.
- Experiment and innovate—leverage AI to enhance customer insights and improve home search and listing experiences.
- Mentor a team of talented machine learning engineers, guiding them in best practices for model development, deployment, and optimization.
- Collaborate with cross-functional teams, including product managers, analysts, data engineers, and leadership, to identify high-impact opportunities and translate them into AI-driven solutions.
- Deploy models at scale using modern cloud platforms (AWS/GCP), containerization (Docker), and ML frameworks like TensorFlow, PyTorch, or JAX.
Other
- 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.
- For most roles, employees work three or more days in our offices.
- Excellent Communication – Ability to articulate ML concepts to both technical and non-technical stakeholders.
