AI Systems Engineer, Architecture


About the Team

The architecture team is responsible for designing the neural network architecture of OpenAI’s flagship language models and has shipped major advances with all of OpenAI's language models since GPT-4. Our work spans the entire spectrum of architecture development and deployment, all the way from the foundational science to the engineering that allows us to train and deploy our models efficiently at scale. Our work has tremendous leverage and deep implications across our stack and we collaborate closely with many other research and engineering teams.

 

About the Role

As a senior engineer for the Architecture Systems Team, you will be an expert on the frameworks used by OpenAI for large-scale training, efficient sampling, architecture and optimization research, and simulating model performance.

You will collaborate closely with both researchers and engineers across the company to integrate new advances into our training and sampling stacks and make foundational improvements to the underlying frameworks. You will own the benchmarking and simulation tools that OpenAI uses to accurately estimate the performance of and design the configuration of new models. You will help set direction for the architecture systems team, mentor more junior members of the team, and help guide the evolution of our ML frameworks.

We’re looking for people who love understanding things at a very deep level, care about both well-designed APIs and systems efficiency, are excited about working at the boundary of research and engineering and collaborating across teams, and who are able to reason across all layers of our stack, from the ML algorithm all the way down to the hardware. Your work will directly impact the capability of our flagship models.

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:

  • Become an expert in the frameworks used by OpenAI for large-scale training, efficient sampling, architecture and optimization research, and simulating model performance 
  • Work with researchers to ship new advances in OpenAI's flagship models
  • Work with the platform teams to make foundational improvements to our ML frameworks

 

You might thrive in this role if you:

  • Love collaborating across teams and working at the boundary of engineering and research
  • Care about both well-designed APIs and systems efficiency
  • Have experience with the systems and frameworks used in LLM training and deployment
  • Love understanding and debugging systems across all layers of abstraction
  • Have strong software engineering skills and are proficient in Python

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. 

OpenAI Affirmative Action and Equal Employment Opportunity Policy Statement

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.

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.

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