Realtor.com is looking to build intelligent systems that optimize pricing, forecasting, and recommendation engines to improve their understanding of their customer portfolio and drive revenue growth.
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.
- Strong Creative Thinking & Problem-Solving Skills – Passion for tackling complex business challenges, improving customer experience, and driving measurable impact.
- Excellent Communication – Ability to articulate ML concepts to both technical and non-technical stakeholders.
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
- Lead the full ML lifecycle to design and deploy cutting-edge models that directly drive revenue and improve customer experiences.
- Mentor talented engineers in an environment where people are our foundation and you’re trusted to own and innovate.
- 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.
- Play a key role in mentoring and shaping the ML strategy for a growing team.
- We foster an agile, experimentation-driven culture that rewards curiosity and bold ideas.
