MLOps Engineer

About the role

Zof AI is seeking a MLOps Engineer to own the platform our AI systems run on. This is a consolidated platform role spanning what the market posts as AI Infrastructure, MLOps, LLMOps, and agent platform engineering: model serving and scaling, GPU and compute efficiency, and the provisioning, observability, and reliability infrastructure that keeps production agents stable. The ideal candidate has operated real AI workloads in production and builds infrastructure that lets a small team run systems well above its weight.

Responsibilities

• Design and operate model serving, scaling, and compute infrastructure.
• Own GPU and inference efficiency, capacity, and cost.
• Build the platform for provisioning, running, and scaling agents.
• Build observability for AI systems: tracing, monitoring, and alerting.
• Keep production AI systems stable, debuggable, and recoverable.
• Automate deployment, rollback, and environment management.
• Set reliability standards and incident practices for AI workloads.
• Partner with engineers to make the platform fast to build on.

Requirements

• Experience operating production AI, ML, or high-scale backend systems.
• Strong infrastructure and systems engineering foundation.
• Experience with cloud platforms, containers, and orchestration.
• Experience with observability and reliability tooling.
• Judgment about cost, performance, and operational trade-offs.
• Clear written and verbal communication.
• Comfort operating in a fast-moving environment.
• High ownership of systems in production.

Qualifications

• Experience with GPU clusters, inference servers, or model gateways.
• Experience running agent workloads or long-lived AI processes.
• Experience with Kubernetes, Terraform, or similar tooling.
• Experience in early-stage platform teams.
• AI Infrastructure
• MLOps
• LLMOps
• Agent Platform
• Reliability

Benefits

• MacBook Pro
• Premium AI development tools
  • Cursor Ultra
  • Claude Code Ultra
  • OpenAI Codex Max or equivalent advanced AI tooling
• Access to a high-performance AI product environment
• Close collaboration with leadership, engineering, and customers
• Opportunity to work in the San Francisco AI ecosystem
• Wellness and productivity support where applicable
• Competitive startup environment
• High ownership
• Direct product impact

Benefits may depend on role and final offer terms.

Pay

Competitive salary Plus meaningful equity