Machine Learning Engineer

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Description

We are seeking a skilledmachine learning platform engineer (MLOps) to join our agile platform teamwhich is part of our ML & AI ART. You drive the orchestration of advancedagentic workflows to enable autonomous, AI-driven systems. You will beresponsible for engineering robust data pipelines, establishing comprehensivemodel management lifecycles, overseeing all foundational platform-level AIintegrations – including engineering a robust library of AI skills for agentuse. Design, develop and deploy machine learningsolutions and services Implement end-to-end machine learningpipelines from data ingestion to training and model serving Operationalize LLMs, embeddings, andmulti-agent systems in real-world applications Manage the machine learning and modellifecycle (experimentation, registry, deployment) Oversee the model promotion lifecycle,coordinating validation gates and approval workflows to safely deploy new modelversions from stating to production Containerize applications using Docker andorchestrate them via Kubernetes Build and maintain CI/CD pipelines for MLmodels and LLM applications Design and implement production grade RAGsystems Advanced proficiency in Python programming with a focus on writing clean, testable and efficient code DevOps & Containers: Proficient with Docker for containerization and working knowledge of Kubernetes (k8s) for orchestration Practical understanding of GPU architecture and cloud compute instances to optimize resource allocation for training and i

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