Software Engineer, GPU Infrastructure at OpenAI San Francisco, CA

Qualifications

• Have experience with hyperscale compute systems
• Possess strong programming skills
• Have experience working in public clouds (especially Azure)
• Have experience working in Kubernetes
• Execution focused mentality paired with a rigorous focus on user requirements
• As a bonus, have an understanding of AI/ML workloads

Benefits

• $325K – $590K
• The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience
• In addition to the salary range listed above, total compensation also includes generous equity and benefits
• Medical, dental, and vision insurance for you and your family
• Mental health and wellness support
• 401(k) plan with 50% matching
• Generous time off, many company holidays, and multiple coordinated company office closures throughout the year for focus and recharge
• Paid parental leave (24 weeks paid birth-parent leave & 20-week paid parental leave) and family-planning support
• Annual learning & development stipend ($1,500 per year)

Responsibilities

• The fleet team focuses on running the world’s largest, most reliable, and frictionless GPU fleet to support OpenAI’s general purpose model training and deployment
• Work on this team ranges from
• Maximizing GPUs doing useful work by building user-friendly scheduling and quota systems
• Running a reliable and low maintenance platform by building push-button automation for kubernetes cluster provisioning and upgrades
• Supporting research workflows with service frameworks and deployment systems
• Ensuring fast model startup times though high performance snapshot delivery across blob storage down to hardware caching
• As an engineer within Fleet infrastructure, you will design, write, deploy, and operate infrastructure systems for model deployment and training on one of the world’s largest GPU fleet
• Design, implement and operate components of our compute fleet including job scheduling, cluster management, snapshot delivery, and CI/CD systems
• Interface with researchers and product teams to understand workload requirements
• Collaborate with hardware, infrastructure, and business teams to provide a high utilization and high reliability service

Full Description

Software Engineer, GPU Infrastructure job at OpenAI. San Francisco, CA.

This role will support the fleet infrastructure team at OpenAI. The fleet team focuses on running the world’s largest, most reliable, and frictionless GPU fleet to support OpenAI’s general purpose model training and deployment. Work on this team ranges from

• Maximizing GPUs doing useful work by building user-friendly schedul

ing and quota systems

• Running a reliable and low maintenance platform by building push-button automation for kubernetes cluster provisioning and upgrades

• Supporting research workflows with service frameworks and deployment systems

• Ensuring fast model startup times though high performance snapshot delivery across blob storage down to hardware caching

• Much more!

About the Role

As an engineer within Fleet infrastructure, you will design, write, deploy, and operate infrastructure systems for model deployment and training on one of the world’s largest GPU fleet. The scale is immense, the timelines are tight, and the organization is moving fast; this is an opportunity to shape a critical system in support of OpenAI's mission to advance AI capabilities responsibly.

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 to new employees.

In this role, you will:

• Design, implement and operate components of our compute fleet including job scheduling, cluster management, snapshot delivery, and CI/CD systems.

• Interface with researchers and product teams to understand workload requirements

• Collaborate with hardware, infrastructure, and business teams to provide a high utilization and high reliability service

You might thrive in this role if you:

• Have experience with hyperscale compute systems

• Possess strong programming skills

• Have experience working in public clouds (especially Azure)

• Have experience working in Kubernetes

• Execution focused mentality paired with a rigorous focus on user requirements

• As a bonus, have an understanding of AI/ML workloads

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 do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or any other legally protected status.

For US Based Candidates: Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records.

We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link .

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.

Compensation

$325K – $590K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience.

In addition to the salary range listed above, total compensation also includes generous equity and benefits.

• Medical, dental, and vision insurance for you and your family

• Mental health and wellness support

• 401(k) plan with 50% matching

• Generous time off, many company holidays, and multiple coordinated company office closures throughout the year for focus and recharge.

• Paid parental leave (24 weeks paid birth-parent leave & 20-week paid parental leave) and family-planning support

• Annual learning & development stipend ($1,500 per year)