Performance Modeling Engineer

OpenAI•San Francisco, CA

1d•Hybrid

About The Position

OpenAI’s Hardware organization develops system and infrastructure solutions designed for the unique demands of advanced AI workloads. They work closely with architecture, infrastructure, and vendor teams to evaluate system performance and guide critical design decisions. The team focuses on building and applying performance modeling frameworks to understand system behavior, quantify tradeoffs, and inform next-generation infrastructure design. The role involves developing and applying modeling tools that evaluate AI system performance and inform architectural decisions. You will work closely with the Performance Modeling Lead and partner teams to analyze system behavior, run simulations or analytical models, and help quantify tradeoffs across compute, memory, networking, and storage. You will contribute to building modeling frameworks and applying them to real-world questions that impact system design and vendor decisions. This role is well-suited for engineers with strong software or modeling backgrounds who are interested in developing deeper expertise in system architecture and AI infrastructure. This role is based in San Francisco, CA, and uses a hybrid work model of 3 days in the office per week.

Requirements

Strong software engineering or modeling background (e.g., simulation, systems modeling, or performance analysis).
Familiarity with system architecture fundamentals (compute, memory, networking).
Experience with programming and building technical tools or frameworks.
Ability to reason about performance bottlenecks and scaling behavior.
Strong analytical skills and comfort working with quantitative models.
Ability to collaborate across teams and learn new system domains quickly.

Nice To Haves

Exposure to AI/ML workloads or distributed systems.
Experience with simulation tools, performance modeling, or systems analysis.
Familiarity with data center infrastructure or large-scale systems.
Experience working with performance data, benchmarking, or profiling tools.
Interest in system architecture and hardware/software co-design.

Responsibilities

Develop and maintain performance modeling tools and frameworks.
Build models to evaluate system behavior across: compute, memory, and interconnect subsystems; distributed system scaling and bottlenecks.
Run simulations and analytical models to support architectural tradeoff analysis.
Collaborate with performance modeling lead and system architects to answer forward-looking design questions.
Analyze and interpret modeling outputs, translating results into actionable insights.
Validate models against real system measurements and workload behavior.
Contribute to improving modeling fidelity, usability, and scalability.