MLOps Jobs

I want a working proof-of-concept application that pulls together a modern MLOps stack on Kubernetes. The build should spin up from a clean repo, flow through a CI/CD pipeline, and deploy an end-to-end demo that highlights three AI pillars I care about: Nvidia AI Enterprise for accelerated inference and training, production-grade LLM functionality (LangChain-powered), and Retrieval-Augmented Generation using a vector store. Core workflow • Code is pushed → pipeline (GitHub Actions or similar) runs tests, builds the container image, and promotes it to the cluster. • Helm or ArgoCD handles drift management so that the desired state remains in sync. • At runtime, the service must auto-scale both CPU and GPU requests, proving horizontal and vertical elasticity. &bu...

should Build agentic workflows using LangChain/LangGraph and similar frameworks. • Develop autonomous agents for data validation, reporting, document processing, and domain workflows. • Deploy scalable, resilient agent pipelines with monitoring and evaluation. GenAI Application Engineering • Develop GenAI applications using models like GPT, Gemini, and LLaMA. • Implement RAG, vector search, prompt orchestration, and model evaluation. • Partner with data scientists to productionize POCs. Data & Platform Engineering • Build distributed data pipelines (Python, PySpark). • Develop APIs, SDKs, and integration layers for AI-powered applications. • Optimize systems for performance and scalability across cloud/hybrid environments. MLOps / LLMOps • C...