AI Infrastructure Engineer

present of AI; San Francisco (CA); On-site; USD 150,000 - 230,000; Full time

Job summary

PlayerZero builds a living model of production software to predict and prevent customer-facing issues before code ships. The AI infrastructure engineer role focuses on keeping model serving systems fast, reliable, and cost-efficient while supporting evolving ML workloads.

You will work close to AI development, deploying models behind APIs, tracking performance, and improving pipelines for scalable inference and monitoring in production.

Qualifications

• Solid software engineering fundamentals and production-grade coding practices.
• Hands-on cloud experience and familiarity with containerized deployments.
• Working grasp of model serving and data pipelines to support ML workloads.

Responsibilities

• Build and run systems that train, serve and monitor models.
• Focus on reliability, cost and speed of inference and training pipelines.
• Collaborate with teams to maintain scalable, observable infrastructure.

Skills

Software engineering

Cloud experience

Container technologies

Model serving

Data pipelines

Tools

Cloud platforms

Container technologies

Job description

An AI Infrastructure Engineer typically builds and runs the systems that train, serve and monitor machine learning models, with a focus on reliability, cost and speed. A strong candidate brings solid software engineering, hands on cloud and container experience, and a working grasp of model serving and data pipelines. At a company building a model of production software to catch issues before code ships, that work likely means keeping prediction systems fast and dependable.

How it fits the AI era

This role sits close to the core of AI work, since the infrastructure behind models decides whether they are useful in practice. AI tools now help write and tune that infrastructure, but judgment about reliability, failure modes and tradeoffs stays human. The job is less about training one model and more about keeping many systems running well.

How it builds AI experience

The role offers direct experience running models in production, from serving and monitoring to cost control and scaling. Building that background can start with small projects that deploy a model behind an API and track its behavior over time. Working on developer tools that predict software issues adds a practical angle on applying AI to real engineering problems.

Worth showing

• Model serving at scale
• Cloud and containers
• Monitoring and reliability
• Strong software engineering

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About PlayerZero

PlayerZero builds a living model of production software to predict and prevent customer-facing issues before code ships, per the company.