Posted:4 hours ago|
Platform:
Hybrid
Full Time
'* Design and manage CI/CD pipelines for ML model deployment.
* Provision and maintain scalable infrastructure using Kubernetes, Docker, AWS Lambda, or cloud services (AWS/GCP/Azure).
* Automate model deployment workflows, ensuring reproducibility and version control.
* Implement monitoring, alerting, and observability for ML systems (latency, throughput, data drift, failures).
* Integrate with model orchestration pipelines (Airflow, Prefect) to support retraining and inference workflows.
* Manage model registry, versioning, and rollout strategies (blue/green, canary deployments).
* Ensure security, compliance, and cost optimization for ML infra.
* Manage vector databases (Opensearch, Pinecone, FAISS, Milvus) for GenAI retrieval pipelines.
* Work closely with ML Engineers and Data Scientists to understand model requirements.
* Support real-time and batch inference pipelines by ensuring infra scalability and resilience.
* Troubleshoot deployment and runtime issues across containers, APIs, and cloud services.
* Document and standardize infrastructure-as-code practices (Terraform, Helm, etc.).
* Manage GPU/accelerator infra for LLM fine-tuning or inference optimization.
.
Professional Degree: Any B.E/B.Tech
Mandatory Certification: Machine Learning or Data Science.
Managerial & Leadership Responsibilities: 'Leading a team of 4 Data scientist and ML engineers to deliver on primary and secondary responsiblities..
Cloudxtreme
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