Distributed Training Engineer
Software EngineeringPosted 15 Mar 2024
Advertised as “Distributed Training Engineer, Sora”
Posted 15 Mar 2024
Advertised as “Distributed Training Engineer, Sora”
The original posting with the fluff stripped out
| Base salary | US$293,000 – US$490,000 / yr |
|---|
About the Team
The Sora team is working on making video a key capability of OpenAI’s foundation models. We are a hybrid research and product team that seeks to understand and expand the capabilities of our video models, while ensuring their reliability and safety. We accomplish this both through directly studying and experimenting with the models, as well as deploying them into the real-world to distribute their benefits widely.
About the Role
As a Distributed Systems/ML engineer, you will work on improving the training throughput for our internal training framework and enable researchers to experiment with new ideas. This requires good engineering (for example designing, implementing, and optimizing state-of-the-art AI models), writing bug-free machine learning code (surprisingly difficult!), and acquiring deep knowledge of the performance of supercomputers. We’re looking for people who love optimizing performance, understanding distributed systems, and who cannot stand having bugs in their code.
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:
Collaborate with researchers to enable them to develop systems-efficient video models and architectures
Apply the latest techniques to our internal training framework to achieve impressive hardware efficiency for our training runs
Profile and optimize our training framework
You might thrive in this role if you:
Have experience working with multi-modal ML pipelines
Love diving deep into systems implementations and understanding their fundamentals in order to improve their performance and maintainability
Have strong software engineering skills and are proficient in Python.
Have experience understanding and optimizing training kernels
Are passionate about understanding stable training dynamics
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.
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