Sr. Machine Learning Engineer

Realtor.com Careers•Austin, TX

1d•Hybrid

About The Position

The ML Platform team powers all machine learning experiences across Realtor.com® 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.

Requirements

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
Bachelor's or Master's degree in Computer Science, Engineering, or equivalent professional experience.

Nice To Haves

Experience with recommender systems, personalization, or search ranking is a strong plus

Responsibilities

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