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HomeCompaniesOpenAIPerformance Modeling Engineer ~2

Performance Modeling Engineer ~2

OpenAI · San Francisco · Hybrid · Active · Ashby

Job facts

FieldValue
CompanyOpenAI
TitlePerformance Modeling Engineer ~2
Normalized title-
Department / teamScaling / Scaling, Compute, Hardware
LocationSan Francisco, CA, United States
Work modelHybrid / Hybrid
Employment typeFull Time
Salary-
Statusactive
ATS providerAshby
Posted / first seen / 2026-05-29
Changed / last seen2026-05-29 / 2026-06-06

Related slices

PageWhat it containsOpen
Company jobsActive postings from OpenAI.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through Ashby.Open
Provider filtered searchThe same provider as a filtered job collection.Open
City jobsActive postings in San Francisco.Open
Department jobsActive postings in Scaling.Open
Work model jobsActive Hybrid postings.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyOpenAI
Source0cd4593e-8bd2-40af-a7c0-80a50e54698b
ATS providerAshby

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 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 damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form . No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link . OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

Full job record

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Org IDc221c23f-16cb-4ca1-b4cf-11e90e650a62
Source ID0cd4593e-8bd2-40af-a7c0-80a50e54698b
Board ID0cd4593e-8bd2-40af-a7c0-80a50e54698b
Providerashby
Provider Job Key4f6be73e-9a1d-4ec6-8b0e-b2af0b4becfb
TitlePerformance Modeling Engineer ~2
Normalized Title
Statusactive
Activeyes
Location TextSan Francisco
DepartmentScaling
TeamScaling, Compute, Hardware
Employment Typefull_time
Workplace Typehybrid
Remote Policyhybrid
CountryUnited States
RegionCA
CitySan Francisco
Salary Raw
Salary Min
Salary Max
Salary Currency
Salary Period
Source URLhttps://jobs.ashbyhq.com/openai/4f6be73e-9a1d-4ec6-8b0e-b2af0b4becfb
Apply URLhttps://jobs.ashbyhq.com/openai/4f6be73e-9a1d-4ec6-8b0e-b2af0b4becfb/application
First Seen At2026-05-29 05:23:29Z
Last Seen At2026-06-06 19:14:33Z
Last Checked At2026-06-06 19:14:33Z
Last Changed At2026-05-29 05:23:29Z
Inactive At
Source Posted At
Source Updated At
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=ashby/board=openai/date=2026-06-06/2026-06-06T19-07-10-217Z-546cfa69b1194ed1036069c84088321e27543dfc6a81b7979bc13c3350d33d85.json
Event Fields
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Parsed Structured
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Extensions
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Native Structured
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