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