ML Ops Engineer — Equity & AI Infra Architect

Fabrion; San Francisco (CA); On-site; USD 120,000 - 150,000; Full time

Benefits offered by this job

Competitive salary

Meaningful equity

Job summary

A pioneering AI company in the San Francisco Bay Area is seeking an ML Ops Engineer to automate model training, deployment, and governance processes. The ideal candidate will have extensive MLOps experience and be proficient in tools like Kubernetes and Terraform. This role offers a competitive salary along with equity opportunities, perfect for those looking to contribute to groundbreaking AI infrastructure.

Qualifications

• 4+ years in MLOps or ML platform engineering.
• Experience with model management tools like MLflow and Weights & Biases.
• Familiarity with large model deployments and tuning libraries.

Responsibilities

• Build and maintain automated pipelines for model training and deployment.
• Manage hybrid compute infrastructure for training and inference.
• Implement and enforce model governance and observability.

Skills

MLOps experience

Model lifecycle management

Container orchestration

Automating pipelines

Infrastructure management

Tools

Kubernetes

Terraform

Docker

Ray

GitHub Actions

Job description

A pioneering AI company in the San Francisco Bay Area is seeking an ML Ops Engineer to automate model training, deployment, and governance processes. The ideal candidate will have extensive MLOps experience and be proficient in tools like Kubernetes and Terraform. This role offers a competitive salary along with equity opportunities, perfect for those looking to contribute to groundbreaking AI infrastructure.