Performance Modeling Lead

OpenAI; San Francisco (CA); Hybrid; USD 342,000 - 555,000; Full time

Job summary

OpenAI is looking for a Performance Modeling Lead in San Francisco to build a high-impact team focused on AI infrastructure systems. This role involves developing modeling frameworks and methodologies that inform architectural decisions.

The ideal candidate will have expertise in AI/ML workloads, strong communication skills, and experience leading teams. OpenAI offers a hybrid work model with relocation assistance and a competitive compensation range of $342K – $555K.

Qualifications

• Experience owning or building performance modeling frameworks used to drive real system design decisions.
• Deep knowledge of AI/ML workloads, including training and/or inference at scale.
• Experience using modeling to inform architectural decisions.

Responsibilities

• Build and own a performance modeling framework/toolchain to evaluate AI systems.
• Analyze and quantify architectural tradeoffs across compute, memory, networking, and storage.
• Lead and grow a small team, maintaining high standards for modeling rigor.

Skills

Performance modeling frameworks

AI/ML workloads

System-level tradeoffs

Clear communication

Analytical or simulation modeling

Job description

About The Team

OpenAI’s Hardware organization develops system and infrastructure solutions designed for the unique demands of advanced AI workloads. We work closely with research, software, and external hardware partners to shape the next generation of AI systems, from silicon through full‑scale deployments. Our team focuses on understanding and optimizing performance across the full system stack—ensuring that architectural decisions are grounded in rigorous, quantitative analysis of real‑world workloads.

About The Role

We are seeking a Performance Modeling Lead to build and lead a small, high‑impact team responsible for answering forward‑looking architectural questions across AI infrastructure systems. You will develop modeling frameworks and methodologies to evaluate system‑level tradeoffs and guide key design decisions. Your work will directly influence reference architectures, vendor designs, and long‑term infrastructure strategy. This role sits at the intersection of AI workloads, system architecture, and quantitative modeling, and requires strong technical judgment, ownership, and the ability to translate complex analysis into clear, actionable guidance. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance.

Key Responsibilities

• Build and own a performance modeling framework/toolchain to evaluate AI systems across multiple levels of abstraction.
• Analyze and quantify architectural tradeoffs across compute, memory, networking, storage, and system topology.
• Develop performance models to guide decisions on:
  • scale‑up vs. scale‑out architectures
  • interconnect and network design
  • memory hierarchy and system balance.
• Translate modeling outputs into clear recommendations for internal teams and external hardware vendors.
• Influence reference designs and vendor roadmaps through data‑driven insights.
• Partner closely with machine learning, systems, and hardware teams to understand workload characteristics and requirements.
• Lead and grow a small team (2–3 engineers), setting technical direction and maintaining high standards for modeling rigor.
• Continuously improve modeling fidelity by validating against real system behavior and measurements.

Qualifications

• Experience owning or building performance modeling frameworks used to drive real system design decisions.
• Deep knowledge of AI/ML workloads, including training and/or inference at scale.
• Understanding of system‑level tradeoffs across compute, memory, and networking in large‑scale distributed systems.
• Comfortable working across abstraction layers—from workload behavior to hardware implementation.
• Experience using modeling (analytical or simulation) to inform architectural decisions.
• Ability to operate in ambiguous problem spaces and turn open‑ended questions into structured analysis.
• Clear communication and influence skills for both internal teams and external partners.

Preferred Skills

• Experience working with hardware vendors (ODM/JDM, silicon, networking).
• Background in data center infrastructure or hyperscale systems.
• Familiarity with accelerators (GPUs/ASICs) and interconnects (e.g., NVLink, InfiniBand, Ethernet).
• Experience influencing hardware roadmaps or reference architectures.
• Prior experience leading or mentoring engineers.

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.

Equal Opportunity Employer

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. Background checks for applicants will be administered in accordance with applicable law. We are committed to providing reasonable accommodations to applicants with disabilities. Compensation Range: $342K – $555K.