Intermediate / Senior – MLOps – Python, ML Frameworks, MLOps, Containerization, Terraform, GCP, Vertex AI, IBM Watsonx
IN - TDC 1 (IN110), India
INR 2500K-3500K (estimate) Mid-level Full Time
Tasks
- Build and scale ML pipelines using Vertex AI Pipelines Kubeflow Airflow
- Collaborate with product managers DS and engineers to translate business problems into ML systems
- Contribute to ML platform architecture design and technical roadmap
- Design deploy and maintain ML models and pipelines
- Develop CI/CD workflows for ML
- Drive adoption of MLOps best practices
- Ensure pipelines are secure compliant and cost optimized
- Implement automated retraining, drift detection, and re-deployment
- Implement model monitoring observability and alerting
- Integrate and manage feature stores knowledge graphs and vector databases
- Mentor junior engineers
Perks/Benefits
- N/A
Skills/Tech-stack
Airflow | Deep learning architectures | Docker | EvidentlyAI | Flink | Grafana | Hadoop | Helm | Hive | Kafka | Knowledge of ML | Knowledge of ML algorithms | Knowledge of ML algorithms deep learning architectures | Kubernetes | Learning architectures | Lineage Tracking | Model Governance | Model Monitoring | Prometheus | PyTorch | Python | SQL | Scikit-learn | Spark | TensorFlow | Terraform | Versioning | WatsonX | XGBoost
Education
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