Key Responsibilities
- Design, build, and maintain MLOps pipelines to support AI/ML and agent-based systems
- Automate model training, deployment, monitoring, and versioning using MLflow and related tools
- Collaborate closely with DevOps and engineering teams to streamline CI/CD for ML workflows
- Support the development and deployment of Agentic AI solutions
- Ensure scalability, reliability, and observability of ML systems in production environments
Required Skills & Experience
- Strong experience in Python and software engineering best practices
- Hands-on experience with DevOps / MLOpstools (CI/CD, containerization, orchestration)
- Demonstrated experience working with Databricks is required.
- Experience with MLflow or similar model lifecycle management tools
- Brief understanding of Classical ML and/or Deep Learning algorithms
- Familiarity with Agentic AI concepts or intelligent automation systems
Nice to Have
- Experience deploying ML systems in cloud or enterprise environments
- Exposure to large-scale automation or platform engineering projects
