MLOps Engineer

Maaze Underwriting Solutions

5 - 10 years

12 - 20 Lacs

hyderabad

Posted:22 hours ago| Platform:

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Skills Required

prometheus & grafana kubeflow nvidia gpu architecture devops azure devops

Work Mode

Hybrid

Job Type

Full Time

Job Description

Role & responsibilities

Design and implement MLOps pipelines using
Kubeflow
and
KServe
for model deployment and serving
Deploy and manage production ML models on Kubernetes with
NVIDIA GPU
acceleration
Optimize model inference using
vLLM, TensorRT-LLM, Triton Inference Server
, and
PyTorch Dynamo
Implement auto-scaling using
KEDA, HPA
, and
Azure Cluster Autoscaler
Build
CI/CD pipelines
using
Azure DevOps
for automated ML model deployment
Manage
Azure infrastructure
(AKS, Azure ML, Container Registry) using IaC (Terraform/ARM/Bicep)
Implement monitoring and observability using
Prometheus
and
Grafana
Perform
Linux system administration
and optimize containerized workloads
Deploy and manage
LLM
applications with
OpenAI API
and Azure OpenAI services
Monitor GPU utilization, model performance, and implement drift detection
Build RAG systems and manage vector databases for LLM applications

Preferred candidate profile

Azure certifications (AZ-104, AZ-400, AI-102)
Experience with MLflow or experiment tracking tools
Model optimization techniques (quantization, pruning)
Infrastructure as code expertise (Terraform preferred)
Open-source contributions to ML/MLOps projects

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