Senior MLOps Engineer (DevOps) | 6-9 Y | Bangalore (Hybrid) 3 Days Office | Quick Joiner |

We're looking for an experienced MLOps Engineer to drive ML automation, deployment and platform reliability.
Senior MLOps Engineer (DevOps) | 6-9 Y | Bangalore (Hybrid) 3 Days Office | Quick Joiner |
Key Technical Skills:
DevOps & Cloud Infrastructure
Python, Bash / Go
Docker and Kubernetes
AWS / Azure / GCP
Terraform, Pulumi or CloudFormation
CI/CD & ML Pipelines
GitHub Actions, GitLab CI, Jenkins or Argo Workflows
Kubeflow, Airflow, Prefect or Metaflow
Automated model testing, versioning and deployment
Canary deployments and ML workflow automation
Model Deployment & Serving
TorchServe, NVIDIA Triton, TensorFlow Serving
Seldon, BentoML or similar
Batch and real-time model serving
Monitoring & MLOps
Prometheus, Grafana, Datadog
MLflow, Weights & Biases or Neptune
Model monitoring, data drift and performance tracking
Feature stores – Feast / Tecton
Data versioning – DVC / LakeFS
Key Responsibilities:
Build and manage end-to-end ML pipelines.
Automate model training, validation and deployment.
Develop robust CI/CD pipelines for ML workflows.
Manage scalable Kubernetes-based ML infrastructure and GPU clusters.
Implement model monitoring, observability and alerting.
Maintain experiment tracking, model registries and data lineage.
Optimize cloud infrastructure performance and costs.
Collaborate with Data Science teams to accelerate production AI/ML deployments.
Good to Have:
Experience with GPU infrastructure and distributed ML workloads.
Exposure to LLM deployment, Vector Databases and RAG infrastructure.
Experience with feature stores and data governance.
Ideal Candidate: A hands-on MLOps / DevOps professional with strong cloud, Kubernetes, CI/CD and ML infrastructure expertise, capable of building reliable and scalable production ML platforms.

Skills
Python, Git, AWS, Azure, GCP, Docker, Kubernetes

Experience
5+ yrs

Work arrangement
No