onsite
Lead MLOps Engineer - NTT Data Americas, Inc.
MLOps Engineer
Lead the design and deployment of scalable machine learning pipelines using Python, Docker, Kubernetes, and AWS, driving continuous integration and delivery with MLflow and advanced CI/CD practices.
About the role
Key Responsibilities
- Architect and maintain end‑to‑end MLOps pipelines that support rapid experimentation and production deployment of machine learning models.
- Lead the implementation of containerization (Docker) and orchestration (Kubernetes) strategies for scalable model serving.
- Design and enforce CI/CD workflows, integrating automated testing, model validation, and version control across data, code, and model artifacts.
- Collaborate with data scientists, software engineers, and DevOps teams to ensure seamless model lifecycle management and observability.
- Drive best practices for cloud infrastructure (AWS) including cost optimization, security, and compliance.
Requirements
- 5+ years of experience in MLOps or related roles, with a proven track record of deploying production‑grade ML systems.
- Strong proficiency in Python, Docker, Kubernetes, and CI/CD tooling (GitHub Actions, Jenkins, ArgoCD).
- Hands‑on experience with AWS services (EKS, S3, SageMaker, Lambda) and MLflow or equivalent model management platforms.
- Excellent problem‑solving skills, ability to mentor junior engineers, and strong communication across cross‑functional teams.
- Knowledge of security best practices, monitoring, and logging for ML workloads.
Skills
mlopspythondockerkubernetescicdawsmlflow