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Lead MLOps Engineer - NTT DATA
MLOps Engineer
Lead the design and deployment of scalable machine learning pipelines using Python, Docker, Kubernetes, and CI/CD practices on AWS, driving production readiness and continuous improvement of AI models.
About the role
Key Responsibilities
- Architect and maintain end‑to‑end MLOps pipelines, from data ingestion to model serving, ensuring reliability and scalability.
- Collaborate with data scientists to translate research prototypes into production‑ready services.
- Implement CI/CD workflows for model training, validation, and deployment using Git, Jenkins, or equivalent tools.
- Manage containerized environments with Docker and orchestrate workloads on Kubernetes clusters.
- Monitor model performance in production, set up alerting, and drive automated retraining cycles.
- Mentor junior engineers and promote best practices in code quality, testing, and documentation.
Requirements
- 5+ years of experience in MLOps or related roles, with a strong background in Python and machine learning frameworks.
- Proven expertise in Docker, Kubernetes, and cloud platforms (AWS preferred).
- Hands‑on experience with CI/CD pipelines and automated testing for ML workflows.
- Excellent problem‑solving skills and ability to work cross‑functionally with data science, DevOps, and product teams.
- Strong communication skills and a passion for continuous learning and process improvement.
Skills
pythonmachine learningmlopsdockerkubernetescicdaws