Job Description
Job Summary:
We're seeking a highly experienced
Principal MLOps Engineer (5–10 years)
to lead the design, deployment, and optimization of scalable machine learning infrastructure. This role is ideal for someone with deep expertise in
Kubernetes, cloud-native platforms, and production-grade ML systems
who is passionate about driving MLOps best practices and enabling impactful AI solutions.
Key Responsibilities:
- Architect, build, and maintain scalable MLOps pipelines for model training, deployment, and monitoring
- Lead containerized ML deployments using
Kubernetes (K8s) - Partner with data scientists and engineers to productionize ML models
- Automate model lifecycle management (versioning, rollback, monitoring)
- Ensure system reliability, security, and compliance
- Implement infrastructure as code (Terraform, Helm)
- Define and enforce best practices for model governance and reproducibility