Performance Modeling Engineer ~2

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 architecture, infrastructure, and vendor teams to evaluate system performance and guide critical design decisions. Our team focuses on building and applying performance modeling frameworks to understand system behavior, quantify tradeoffs, and support next-generation infrastructure design. About the Role We are seeking an Performance Modeling Engineer to support the development and application of modeling tools used to evaluate AI system performance and inform architectural decisions. In this role, you will partner closely with Senior Performance Modeling Engineers and the Performance Modeling Lead to analyze system behavior, run simulations and analytical models, and help evaluate tradeoffs across compute, memory, networking, and storage. You will contribute to building modeling frameworks while developing a strong foundation in system architecture and AI infrastructure. This role is ideal for early-career engineers with 1–2 years of experience in software engineering, systems analysis, or performance modeling who are excited to grow in large-scale infrastructure and hardware/software systems. 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 - Support the development and maintenance of performance modeling tools and frameworks - Assist in building models to evaluate system behavior across compute, memory, networking, and interconnect subsystems - Help analyze distributed system scaling behavior and identify performance bottlenecks - Run simulations and analytical models to support architecture and infrastructure decisions - Partner with senior engineers to evaluate design tradeoffs across hardware and system components - Interpret modeling outputs and help translate findings into clear recommendations - Validate models using benchmarking data and real system performance measurements - Improve modeling workflows, documentation, and usability for broader team adoption - Collaborate cross-functionally with hardware, infrastructure, and architecture teams - Continuously build technical depth across AI infrastructure, system architecture, and performance analysis Qualifications - 1–2 years of experience in software engineering, systems modeling, performance analysis, or related technical work - Strong programming skills and experience building technical tools, scripts, or frameworks - Familiarity with system architecture fundamentals such as compute, memory, and networking - Ability to reason about system performance, bottlenecks, and scaling behavior - Strong analytical and problem-solving skills with comfort working in quantitative environments - Ability to learn quickly and work effectively across technical teams Preferred Skills - Exposure to AI/ML workloads, distributed systems, or large-scale infrastructure - Experience with simulation tools, benchmarking, profiling, or performance analysis - Familiarity with data center systems, server architecture, or hardware platforms - Interest in system architecture and hardware/software co-design - Internship or early professional experience in performance engineering, infrastructure, or systems design 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. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or dama

1–2 years of experience in software engineering, systems modeling, performance analysis, or related technical work. Strong programming skills and experience building technical tools, scripts, or frameworks. Familiarity with system architecture fundamentals such as compute, memory, and networking. Ability to reason about system performance, bottlenecks, and scaling behavior. Strong analytical and problem-solving skills with comfort working in quantitative environments. Ability to learn quickly and work effectively across technical teams.

Support the development and maintenance of performance modeling tools and frameworks. Assist in building models to evaluate system behavior across compute, memory, networking, and interconnect subsystems. Help analyze distributed system scaling behavior and identify performance bottlenecks. Run simulations and analytical models to support architecture and infrastructure decisions. Partner with senior engineers to evaluate design tradeoffs across hardware and system components. Interpret modeling outputs and help translate findings into clear recommendations. Validate models using benchmarking data and real system performance measurements. Improve modeling workflows, documentation, and usability for broader team adoption. Collaborate cross-functionally with hardware, infrastructure, and architecture teams. Continuously build technical depth across AI infrastructure, system architecture, and performance analysis.