MLOps Engineer
Bengaluru, Karnataka, India
INR 1800K-3000K (estimate) Mid-level Full Time
Tasks
- Build and automate ML workflows
- Build production Python applications
- Design training environments for ML workloads
- Develop scalable model serving APIs
- Implement CI CD pipelines for ML deployments
- Implement cloud security controls for ML workloads
- Manage MLflow experiment tracking
- Manage data movement and ETL with CDC and Spark PySpark
- Monitor model performance and inference latency
- Provision and maintain container orchestration infrastructure
- Provision cloud ML services and pipelines
- Provision secure reproducible cloud infrastructure with Terraform
- Support ML platform migration across GCP and Azure
Perks/Benefits
- N/A
Skills/Tech-stack
AI Model Garden | AI Pipelines | AI Workbench | AKS | API Gateway | Apache Airflow | BigQuery | BigQuery ML | CDC | CI/CD | CUDA | CUDA workloads | Cloud Composer | Cloud platform | Docker | Experiment tracking | FastAPI | Feature Store | Flask | GKE | GPU autoscaling | Google Cloud | Google Cloud Platform | IAM | Inference endpoints | Kubernetes | LLMOps | MLflow | Microsoft Azure | Model Garden | Model Packaging | Model Registry | Prompt versioning | PySpark | Python | Service Controls | Spark | Terraform | Training environments | VPC Service Controls | Vector Databases | Vertex AI | Vertex AI Model Garden | Vertex AI Workbench | Vertex AI pipelines
Education
N/A
Roles
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