PrideLogic

DevOps Engineer

• Build and operate model and inference serving infrastructure
• Own the ML deployment lifecycle
• Operate agentic and LLM workloads in production
• Build reproducible, automated ML pipelines
• Extend infrastructure-as-code to ML systems
• Operate GitOps for ML workloads
• Run ML and AI workloads on multi-tenant Kubernetes
• Own ML reliability and observability
• Drive ML cost efficiency
• Use agentic coding tools for infrastructure and pipeline work

Senior MLOps Engineer – SRE, DevOps

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PrideLogic

Senior MLOps Engineer – SRE, DevOps

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