Eloquentai

AI Engineer, AIOps & Infrastructure

San Francisco. Posted 14 months ago

The role

You will design, build, and optimize scalable AI infrastructure to support enterprise AI agents. You will automate LLMOps and MLOps workflows and optimize GPU workloads.

What you will do

  • Design and build scalable ML infrastructure for deploying and maintaining AI agents in production.
  • Automate LLMOps and MLOps workflows.
  • Optimize GPU and cloud compute workloads.
  • Develop Kubernetes-based solutions, including custom operators for ML model orchestration.
  • Improve system observability and reliability.
  • Work with ML and engineering teams to streamline data pipelines, model serving, and inference optimizations.
  • Ensure security, compliance, and reliability in AI infrastructure.
  • Participate in on-call rotations.

Required qualifications

  • 5+ years of experience in software engineering, MLOps, or infrastructure development.
  • Strong expertise in Kubernetes and experience managing containerized ML workloads.
  • Deep understanding of cloud platforms (AWS, GCP, Azure) and distributed computing.
  • Proficiency in Python, with experience developing services for ML/AI applications.
  • Experience with ML model deployment pipelines, including model serving, inference optimization, and monitoring.
  • Strong problem-solving skills and the ability to work in a high-scale, production-focused AI environment.

Nice to have

  • Familiarity with vector databases, retrieval systems, and RAG architectures
  • Experience with LLMOps, fine-tuning, and deploying large-scale AI models.
  • Experience with GPU workload optimization, ML model parallelization, or distributed training strategies.
  • Experience building infrastructure for AI-powered applications.
  • Contributions to open-source MLOps tools or AI infrastructure projects.
  • Thriving in a fast-moving startup environment and enjoying solving complex technical challenges.

About the company

Eloquent AI is building multimodal, autonomous AI Operators that execute complex workflows. The company is headquartered in San Francisco and is backed by top-tier investors.