MLOps Engineer
Hyderabad, Telangana, India
INR 2500K-3600K (estimate) Senior-level Full Time
Tasks
- Automate data pipeline workflows
- Collaborate across AI and platform teams
- Containerize ML workloads
- Create model serving infrastructure
- Deploy real time and batch inference
- Design ML pipelines
- Establish MLOps best practices
- Implement ML CI/CD
- Implement model monitoring and drift detection
- Maintain artifact registries
- Manage experiment tracking and model versioning
- Manage feature store for training and inference
- Optimize compute costs and inference latency
- Orchestrate ML workloads with Kubernetes
- Set up alerting for model health
Perks/Benefits
- N/A
Skills/Tech-stack
AI Pipelines | AWS SageMaker | Apache Airflow | Artifact Registry | Azure ML | Bash | CI/CD | CloudFormation | Datadog | Docker | Drift Detection | Experiment tracking | Feature Engineering | Feature Store | Git | Go | Google Cloud | Google Cloud Vertex | Google Cloud Vertex AI | Grafana | Helm | Inference Server | Infrastructure as Code | Java | Kubeflow | Kubernetes | ML monitoring | MLflow | Model Deployment | Model Drift | Model Drift Detection | Model Evaluation | Model versioning | Prometheus | Pulumi | Python | TGI | Tensor | Terraform | Torchserve | Triton Inference | Triton Inference Server | VLLM | Vertex AI | Vertex AI pipelines | “as-code”
Education
N/A
Roles
Engineer | MLOps Engineer | Senior MLOps | Senior MLOps Engineer
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