Llmops Engineer

Requirements:

• 10 - 14 years of experience working on ML projects that include a product-building mindset, strong hands-on skills, technical leadership, and leading development teams.
• Model development, training, deployment at scale, and monitoring performance for production use cases.
• Strong knowledge of Python, data engineering, FastAPI, and NLP.
• Knowledge of LangChain, LlamaIndex, LangTrace, Langfuse, LLM evaluation, MLFlow, and BentoML.
• Should have worked on proprietary and open-source LLMs.
• Experience in LLM fine-tuning, including PEFT/CPT.
• Experience in creating agentic AI workflows using frameworks like CrewAI, LangGraph, AutoGen, and Symantec Kernel.
• Experience in performance optimization, RAG, guardrails, AI governance, prompt engineering, evaluation, and observability.
• Experience in GenAI application deployment on cloud and on-premises at scale for production using DevOps practices.
• Experience in DevOps and MLOps.
• Good working knowledge of Kubernetes and Terraform.
• Experience in a minimum of one cloud: AWS / GCP / Azure to deploy AI services.
• Team player with excellent communication and presentation skills.

Skills

Gen AI, Generative AI, Large Language Model, LLM, Llmops, Machine Learning, MLOps, Python