MLOps Engineer

MLOps Engineer to productionize and scale ML and GenAI systems, with a focus on LLM deployment, orchestration, and reliability in production environments.Key Responsibilities Deploy, manage, and scale ML/DL models in productionBuild and operate Kubernetes-based infrastructure for ML workloadsHandle model packaging, serialization, and versioningDesign scalable inference systems (batch and real-time)Deploy and optimize local LLMs (latency, throughput, cost)Build and manage agentic systems with tool integrationDesign and manage LLM memory (short-term, long-term, vector stores)Integrate and manage API gateways for model access, routing, and rate limitingMonitor performance, drift, and system reliabilityRequirements Hands-on experience with ML/DL models and serializationProven experience in model deployment, scaling, and monitoringExperience with local LLM deployment and optimizationSolid understanding of LLM memory patterns (context windows, retrieval, persistence)Experience with API gateways, load balancing, and service routingFamiliarity with GenAI workflows (RAG, orchestration frameworks)Experience building agentic / multi-step LLM systemsProficiency in Python and modern ML/infra tooling#J-18808-Ljbffr