- Docker & Containerization: Strong experience writing and maintaining Dockerfiles for ML training and inference workloads
- CI/CD Pipelines: Hands-on experience building and operating CI/CD pipelines for ML systems (model build, test, deploy, rollback)
- Azure Kubernetes Service (AKS): Production experience deploying, scaling, and operating ML services on AKS including monitoring and troubleshooting
- MLOps & Model Lifecycle: Experience operationalizing ML models end-to-end: training → deployment → monitoring; Strong understanding of model versioning promotion rollback
- Model Serving & Inference :Experience with production inference pipelinesand model serving ;Hands-on experience with NVIDIA Triton Inference Server
Familiarity with ONNX TensorRT PyTorch or TensorFlow Advanced Python skillsforproductionMLsystems;
debugging performance issues across CPU GPU memoryandsystems; -
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ai infrastructure specialist - Noida - beBeeDev
Job title: MLOps Developer
Description
Job Title: AI Infrastructure Specialist
This is a hands-on role for someone who enjoys working at the intersection of machine learning, cloud infrastructure, and distributed systems.
Required Skills and Qualifications
Nice to Have:
-kubernetes tooling Helm GitOpsCUDA / TensorRT optimization Feature stores / vector databases Streaming systemskafka Redis RabbitMQ;
You are responsible forsustainabilityofproductionMLeffects through proactive issue detection response
Think global think BIG visitus
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Infrastructure Specialist
Only for registered members Noida, Uttar Pradesh, India
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Senior Infrastructure Specialist
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Cybersecurity Infrastructure Specialist
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Mainframe Infrastructure Specialist
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IT Infrastructure Specialist Server
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Infrastructure Support Specialist
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