MLOps Engineer
Tasks
- Build CI CD workflows for model development and deployment
- Build feature stores and data pipelines
- Deploy and optimize model serving infrastructure
- Design deployment strategies including A B testing canary releases rollback
- Develop and maintain machine learning pipelines
- Ensure model governance, security, and compliance
- Implement monitoring logging alerting and observability
- Manage cloud resources and infrastructure as code
- Optimize GPU efficiency and enable autoscaling
Perks/Benefits
Skills/Tech-stack
AWS | Bash | Cloud platform | Databricks | Datadog | FastAPI | GitOps | Go | Google Cloud | Google Cloud Platform | Grafana | Helm | KServe | Kubeflow | Kubernetes | MLflow | Microsoft Azure | NVIDIA Triton | OpenTelemetry | Prometheus | PyTorch | Python | Snowflake | TensorFlow | TensorFlow Serving | Terraform | Torchserve | Weights and Biases
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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