Senior MLOps Engineer
Skills
About the role
Position: Senior MLOps Engineer
Location: Jaipur
Work Mode: On-site
Experience: 7+ Years
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.
Strong 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.
Strong understanding of software engineering and system design.
Questions about this role
Want AI Applyd to auto-apply to roles like this?
We tailor your resume per posting, fill the forms, and track replies for you.