About the Role:We're looking for an experienced MLOps Engineer to drive ML automation, deployment and platform reliability.Key Technical Skills:DevOps & Cloud Infrastructure:- Python, Bash / Go- Docker and Kubernetes- AWS / Azure / GCP- Terraform, Pulumi or CloudFormationCI/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 automationModel Deployment & Serving:- TorchServe, NVIDIA Triton, TensorFlow Serving- Seldon, BentoML or similar- Batch and real-time model servingMonitoring & MLOps:- Prometheus, Grafana, Datadog- MLflow, Weights & Biases or Neptune- Model monitoring, data drift and performance tracking- Feature stores - Feast / Tecton- Data versioning - DVC / LakeFSKey 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 robust cloud, Kubernetes, CI/CD and ML infrastructure expertise, capable of building reliable and scalable production ML platforms. (ref:hirist.tech)

📌 Senior MLOps Engineer - DevOps (Bengaluru)
🏢 Twinpacs Sdn Bhd
📍 Bengaluru