Used Tools & Technologies
Machine LearningRequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Distributed Systems @ 3
Networking @ 3
System Architecture @ 6
AI @ 3
Profiling @ 3
Performance Analysis @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
About the Team
OpenAI’s Hardware organization develops system and infrastructure solutions designed for the unique demands of advanced AI workloads. The team works closely with architecture, infrastructure, and vendor teams to evaluate system performance and guide critical design decisions. The Performance Modeling team focuses on building and applying performance modeling frameworks to understand system behavior, quantify tradeoffs, and support next-generation infrastructure design.
About the Role
You will support the development and application of modeling tools used to evaluate AI system performance and inform architectural decisions. Partnering closely with Senior Performance Modeling Engineers and the Performance Modeling Lead, you will 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. The role is based in San Francisco, CA and uses a hybrid work model of 3 days in the office per week. OpenAI offers relocation assistance for this role.
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 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
Benefits
The base pay offered may vary depending on factors including market location, job-related knowledge, skills, and experience. In addition to the listed salary range, total compensation includes equity, potential performance-related bonuses (for eligible employees), and benefits such as:
- Medical, dental, and vision insurance (employer contributions to Health Savings Accounts)
- Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses
- 401(k) retirement plan with employer match
- Paid parental leave and paid medical/caregiver leave
- Flexible PTO (exempt) and paid days off for non-exempt employees
- 13+ paid company holidays and other coordinated office closures
- Mental health and wellness support
- Employer-paid basic life and disability coverage
- Annual learning and development stipend
- Daily meals in offices and meal delivery credits (as eligible)
- Relocation support for eligible employees
Other Information
OpenAI is an equal opportunity employer. Background checks will be administered in accordance with applicable law. Reasonable accommodations for applicants with disabilities are available.