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Tranzeal is seeking a hands-on Senior MLOps Engineer to own the end-to-end deployment, governance and observability of DL models, LLMs and SLMs. The role covers cloud, on-prem, hybrid and air-gapped environments, with a focus on robust model lifecycle management.
You will leverage Python, Databricks or Azure ML, and deploy models using PyTorch/TensorFlow across Kubernetes and GPU infrastructure, ensuring scalable, reliable AI operations.
Experience: 5 Years
We are seeking a hands-on AI Deployment Engineer specializing in ML Engineering, Model Deployment, Model Governance, and Model Observability. The engineer will own the complete lifecycle of Deep Learning models, LLMs, and SLMs across cloud, on-premises, hybrid, and air-gapped environments.
35 years in MLOps, LLMOps, ML Engineering, or AI Engineering.
Strong expertise in model deployment on: