Eloquentai

Eloquentai

AI Engineer, AIOps & Infrastructure

San Francisco

Sponsorship not specifiedDetected 334 days ago
PythonVector DatabasesAWSGCPAzureCloud PlatformsKubernetesMachine LearningData EngineeringLLMsRAGAgentic AILLMOpsMLOpsProblem Solving

About the role

  • Your work will enable machine learning engineers and AI teams to train, fine-tune, and deploy LLMs efficiently while ensuring stability, observability, and performance at scale.
  • You'll play a key role in automating LLMOps and MLOps workflows, optimizing GPU workloads, and ensuring resilient, production-ready AI systems.
  • This role requires deep expertise in cloud infrastructure, Kubernetes, and LLM and ML deployment pipelines.

Responsibilities

  • Design and build scalable ML infrastructure for deploying and maintaining AI agents in production.
  • Develop Kubernetes-based solutions, including custom operators for ML model orchestration.

Requirements

  • 5+ years of experience in software engineering, MLOps, or infrastructure development.
  • Strong expertise in Kubernetes and experience managing containerized ML workloads.
  • 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.
  • You have experience with LLMOps, fine-tuning, and deploying large-scale AI models.

Nice to have

  • Familiarity with vector databases, retrieval systems, and RAG architectures is a plus.

Skills

  • it sees, reads, clicks, types, and makes decisions-transforming how work gets done in regulated, high-stakes environments.
  • Headquartered in San Francisco with a global footprint, Eloquent AI is a fast-growing company backed by top-tier investors.
  • Automate LLMOps and MLOps workflows, ensuring seamless model training, fine-tuning, deployment, and monitoring.

This listing is sourced directly from Eloquentai's careers page and normalized into a canonical job model.