Senior – MLE – Python, ML Frameworks, MLOps, Containerization, Terraform, GCP, Vertex AI, IBM Watsonx

ups

Chennai, India 5 Years Exp Posted 59d ago

Design, deploy, and maintain production-ready ML models and pipelines for real-world applications.
Build and scale ML pipelines using Vertex AI Pipelines, Kubeflow, Airflow, and manage infra-as-code with Terraform/Helm.
Implement automated retraining, drift detection, and re-deployment of ML models.
Develop CI/CD workflows (GitHub Actions, GitLab CI, Jenkins) tailored for ML.
Implement model monitoring, observability, and alerting across accuracy, latency, and cost.
Integrate and manage feature stores, knowledge graphs, and vector databases for advanced ML/RAG use cases.
Ensure pipelines are secure, compliant, and cost-optimized.
Drive adoption of MLOps best practices: develop and maintain workflows to ensure reproducibility, versioning, lineage tracking, governance.
Mentor junior engineers and contribute to long-term ML platform architecture design and technical roadmap.
Stay current with the latest ML research and apply new tools pragmatically to production systems.
- Collaborate with product managers, DS, and engineers to translate business problems into reliable ML systems.