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Lead ML Ops Engineer - Schneider Electric
MLOps Engineer
Lead the design, deployment, and scaling of AI solutions using Python, AWS, Docker, and Kubernetes, turning prototypes into production-grade services while automating workflows and collaborating closely with data scientists.
About the role
Key Responsibilities
- Design, develop, and deploy machine learning models that solve business challenges and unlock new opportunities.
- Build and maintain a robust AI infrastructure on AWS, leveraging Docker, Kubernetes, and CI/CD pipelines to ensure scalable, production‑grade solutions.
- Collaborate with Data Scientists and Analysts to convert prototypes into accessible APIs and minimum viable products.
- Automate data pipelines, model training, and deployment workflows to drive efficiency and reduce time‑to‑market.
- Implement monitoring, logging, and performance tuning for ML services, ensuring reliability and compliance.
Requirements
- 5+ years of experience in ML Ops or related roles, with a strong background in Python and cloud platforms.
- Proficiency in AWS services (SageMaker, ECS/EKS, Lambda), Docker, Kubernetes, and CI/CD tools (GitHub Actions, Jenkins).
- Hands‑on experience with model versioning, MLOps pipelines, and automated testing.
- Excellent problem‑solving skills and the ability to translate business needs into technical solutions.
- Strong communication skills and a collaborative mindset.
Skills
pythonmachine learningawsdockerkubernetescicd