ML Ops Engineer

Responsibilities

• Build and maintain automated pipelines for LLM fine-tuning, RAG, and model deployment
• Manage hybrid compute infrastructure using Kubernetes, Ray, and Terraform
• Implement model governance, observability, and evaluation frameworks

Requirements

• 4+ years in MLOps or ML platform engineering
• Deep familiarity with model lifecycle tools like MLflow, Weights & Biases, and HuggingFace
• Proficiency with Kubernetes, Terraform, and container orchestration

Preferred Qualifications

• Experience with large model deployments (LLaMA, Mistral, Mixtral)
• Familiarity with agent orchestration tools like LangChain or LangGraph
• Experience with inference serving such as vLLM, TGI, or Triton

About the Company

Backed by 8VC, Agentic AI Lab is building intelligent infrastructure through open-source LLMs, agent-native pipelines, and knowledge-graph-grounded models.