AI Infrastructure Engineer, pAGI
At a glance
Mid-level ML Platform & Ops role at OpenAI. San Francisco · full-time · $266,000–$500,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Build and run systems for large-scale model training and evaluation, raising reliability, throughput, and efficient resource use
- Create shared inference and grading services with capacity automation, health checks, and performance visibility
- Adjust compute scheduling and workload resources to cut idle GPU time and restore jobs quickly after failures
- Trace slowdowns in training, inference, and orchestration, then coordinate fixes across teams
- Give researchers self-service experiment tools, automated checks, and observability to compare results with less manual work
What you bring
- You have built or operated distributed systems at large scale and bring strong software engineering skills
- Your background includes ML infrastructure, inference systems, GPU performance, or infrastructure tooling
- You take initiative on open-ended work and use measurements to debug across system boundaries and improve performance
Who this fits
This mid-level, full-time role suits an engineer who enjoys owning infrastructure projects from diagnosis through deployment and operation, while working closely with researchers. It is based in San Francisco and listed as hybrid. The stated annual pay range is $266,000 to $500,000.
From the employer
About the Team
pAGI Infra team builds and operates the systems that make large-scale model training and evaluation reliable, efficient, and easy to run. Our work spans distributed training infrastructure, inference and grading platforms, compute scheduling, and research tooling. We partner closely with researchers and engineering teams to turn new research needs into dependable infrastructure, improve GPU efficiency, and shorten the path from an experiment to a validated model.
About the Role
We’re looking for an AI Systems Engineer to help scale the infrastructure behind our training and evaluation workflows. You’ll own projects from identifying bottlenecks and designing solutions through deployment and operation. The work combines distributed systems engineering, performance optimization, and close collaboration with researchers. You might build a shared grading service, improve resource allocation across workloads, or bring a new training stack into production — directly improving how quickly and reliably research moves forward.
In this role, you will:
Build and operate infrastructure for large-scale training and evaluation, improving reliability, throughput, and resource efficiency.
Develop shared inference and grading platforms with automated capacity management, health monitoring, and visibility into performance.
Improve compute scheduling and resource allocation to reduce idle GPU time and help workloads recover quickly from failures.
Diagnose bottlenecks across training, inference, and orchestration, and work across teams to improve end-to-end performance.
Build self-service tools, automated validation, and observability that help researchers launch experiments, diagnose issues, and compare results with less manual intervention.
You might thrive in this role if you:
Are excited about the potential of personal AGI and want to build the infrastructure that enables it.
Have strong software engineering fundamentals and experience building or operating large-scale distributed systems.
Have experience in ML infrastructure, inference systems, GPU performance, or infrastructure tooling.
Are highly self-motivated and comfortable taking ownership of open-ended problems.
Enjoy debugging across system boundaries and using measurements to guide improvements in performance and reliability.
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.
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