Key Responsibilities
Build and manage end-to-end ML pipelines.
Deploy ML models using CI/CD pipelines.
Develop scalable MLOps infrastructure on AWS, Azure, or GCP.
Automate model training, testing, versioning, and deployment.
Monitor model performance, drift, and data quality.
Collaborate with Data Science and Engineering teams.
Manage Docker and Kubernetes-based deployments.
Optimize and troubleshoot production ML systems.
Required Skills
7+ years of experience in MLOps/ML Engineering/DevOps.
Robust Python programming skills.
Experience with TensorFlow, PyTorch, or Scikit-learn.
Hands-on experience with Docker and Kubernetes.
Experience with AWS, Azure, or GCP.
Knowledge of CI/CD tools (GitHub Actions, GitLab CI, Jenkins, Azure DevOps).
Experience with MLflow, Kubeflow, or Weights & Biases.
Familiarity with ETL pipelines, APIs, Prometheus, Grafana, and ELK.
Robust understanding of software engineering and system design.
📌 Senior Mlops Engineer Jaipur
🏢 Arting Digital
📍 Jaipur
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