onsite
Senior MLOps Technical Lead - HCLTech
Engineering Manager
Senior MLOps Technical Lead driving end‑to‑end ML pipeline automation with MLflow, Kubeflow, and TFX, integrating DevOps practices, Python scripting, and cloud CI/CD to deliver scalable, production‑ready models.
About the role
Key Responsibilities
- Design, build, and maintain robust ML pipelines using MLflow, Kubeflow Pipelines, and TFX, ensuring automated training, validation, and deployment workflows.
- Integrate DevOps practices into ML workflows, leveraging CI/CD pipelines, containerization, and orchestration to accelerate model delivery.
- Collaborate with data scientists and software engineers to translate model prototypes into production‑grade services, focusing on scalability, reliability, and observability.
- Implement monitoring, logging, and alerting for deployed models, ensuring performance drift detection and rapid remediation.
- Architect cloud‑native solutions on major providers (AWS, GCP, Azure), optimizing cost, security, and compliance for ML workloads.
- Mentor and lead cross‑functional teams, fostering best practices in MLOps, code quality, and continuous improvement.
Requirements
- 5+ years of experience in MLOps, DevOps, or related fields, with a strong Python background.
- Hands‑on expertise with MLflow, Kubeflow Pipelines, and TFX, plus containerization (Docker, Kubernetes).
- Proven track record of deploying ML models at scale in cloud environments, with CI/CD implementation.
- Excellent problem‑solving skills, strong communication, and ability to mentor junior engineers.
- Experience with cloud services (AWS, GCP, Azure) and infrastructure‑as‑code tools (Terraform, CloudFormation) is a plus.