We're hiring a Principal MLOps Engineer to lead the design and deployment of scalable, production-grade ML infrastructure.

 

What You'll Do:

Architect and manage end-to-end ML pipelines (data to deployment) Operationalize models for real-time and batch inference Build CI/CD workflows for ML, with automated testing and monitoring Optimize performance and scalability across cloud and containerized environments Lead MLOps best practices and mentor the growing engineering team

What We're Looking For:

7–10 years of experience in ML Engineering or MLOps Strong in Python, Docker, Kubernetes, and CI/CD tools Cloud-native skills (AWS/GCP/Azure) and IaC (Terraform/CDK) Experience with ML platforms like MLflow, Kubeflow, Airflow Deep understanding of model lifecycle, monitoring, and drift detection Bonus: startup experience, real estate/finance domain knowledge, large-scale data tools

Why Join Us:

Competitive compensation + meaningful ESOPs High-impact role with ownership from day one Tech-first culture with strong backing and leadership Solve real problems at scale in a $200B+ industry Hybrid setup with flexibility and fast execution