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Lead AI Engineer
Boost employee efficiency by up to 70% with an AI content assistant that enables conversational search and summarization across secure, private business data.
Experience Requirements:
5+ years of experience in DevOps, SRE, or Cloud Engineering
2+ years focused on MLOps or ML infrastructure
Other Requirements:
Subject matter expertise with cloud platforms (AWS, GCP, or Azure)
Proficiency with ML lifecycle tools such as MLflow, Kubeflow, or SageMaker
Experience with container orchestration (EKS/GKE/AKS) and model serving frameworks
Strong scripting and programming skills in Python, Bash, and YAML
Deep understanding of agentic frameworks
Responsibilities:
Designing and implementing scalable and secure MLOps pipelines
Automating the deployment, monitoring, and governance of machine learning models
Collaborating with Data Scientists and DevOps teams to streamline workflows
Managing and optimizing ML infrastructure including GPU/TPU provisioning
Ensuring reproducibility, traceability, and compliance of ML workflows
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