Sr. Machine Learning Engineer

Recognized as the No.1 site trusted by real estate professionals, ® 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, ® 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. About The Role The ML Platform team powers all machine learning experiences across ® from personalization and recommendations to search ranking, pricing models, and generative AI. As a Senior Machine Learning Engineer, you'll take a leading technical role in building the consumer-facing products and backend services that bring these ML capabilities to millions of users. You'll own the full stack from ML model integration to production APIs, working closely with data scientists, ML engineers, and product teams to ship high-quality, high-impact experiences. Three Reasons To Apply Build next-gen consumer experiences powered by personalization, recommendations, and GenAI for millions of users Work at the intersection of consumer product engineering and cutting-edge ML owning both the user-facing surface and the ML infrastructure behind it Drive the technical direction of a platform that powers every ML-powered feature across ® What You'll Do Serve as a technical lead for key consumer-facing ML initiatives, owning architecture and design across the full stack - from ML model integration to production APIs and user-facing features Design, build, and expose ML-powered capabilities through GraphQL APIs and federated subgraphs, REST endpoints, and event-driven services consumed by web and mobile clients Design, build, and optimize high-performance recommender systems and personalization features, ensuring relevance, accuracy, and speed for millions of users Build and maintain CI/CD pipelines and MLOps workflows using Metaflow and ArgoCD, ensuring reliable, traceable model deployments to production Develop AI-native and GenAI-powered services - including LLM and RAG-based features - that directly improve the consumer experience Own the design and development of data pipelines and the integration of ML models into production web and mobile applications Drive API design best practices across the team - versioning, schema contracts, backwards compatibility, and cross-team API governance Drive performance optimizations across services, ensuring low latency and high availability at scale Collaborate with cross-functional teams - product, ML, data engineering, frontend, and analytics - to define clear API contracts and translate requirements into scalable technical solutions Mentor and coach engineers on best practices, MLOps principles, GraphQL patterns, and production ML integration Contribute to the long-term technical roadmap, driving innovation and reducing technical debt What You'll Bring 7+ years of software engineering experience, with specific expertise in building consumer-facing products powered by ML models Strong hands‑on experience with GraphQL - including federated GraphQL / schema design, and building subgraphs consumed by web and mobile clients Deep experience designing and building RESTful and event-driven APIs at scale, with a strong grasp of API contracts, versioning, and cross-team API governance Hands‑on experience with MLOps tooling - Metaflow, ArgoCD / Argo Workflows, and CI/CD pipelines for ML are required Strong experience with cloud‑native architectures on AWS (Lambda, EC2, S3, EKS, or equivalents) and Kubernetes Proficient in designing and implementing data pipelines and integrating machine learning models into production, user-facing applications Proven experience building with LLMs, RAG, and GenAI - shipping these capabilities into consumer products is required, not a plus Strong communication and collaboration skills - able to drive technical alignment across ML, data science, product, frontend, and engineering teams Experience with recommender systems, personalization, or search ranking is a strong plus Bachelor's or Master's degree in Computer Science, Engineering, or equivalent professional experience How We Work We balance creativity and innovation on a foundation of in-person collaboration. Our employees work three days in our Austin headquarters where they have the opportunity to collaborate in-person, adding richness to our culture and knitting us closer together. How We Reward You ® is committed to investing in the health and wellbeing of our employees and their families. #J-18808-Ljbffr