OpenAISoftware Engineer, Collective Communication
San Francisco · 全职 · 工程与基础设施
需要对标的能力
AI Infra · 推理部署
岗位职责与要求
About the Team
The Workload Networking team is responsible for the collective communication stack used in our largest training jobs. Using a combination of C++ and CUDA we work on novel collective communication techniques that enable efficient training of our flagship models on our largest custom built supercomputers.
The models we train are key ingredients to the AI research progress at OpenAI and the field as a whole, and we continually incorporate learnings from our entire research org into our training platform.
About the Role
As a Software Engineer, Networking you will design and implement custom networking collectives that are tightly integrated into our training stack.
We’re looking for people who have a background in low level performance critical software. Experience with collective communication is a bonus.
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 closely with ML researchers to design and implement efficient collective operations in C++ and CUDA.
- Ensure that our largest training jobs take full advantage of the different network transports used in our supercomputers.
- Work on simulations to inform our future supercomputer network designs.
You might thrive in this role if you:
- Have written distributed algorithms using RDMA in the past.
- Are comfortable writing low level performance sensitive CPU and/or GPU code.
- Are familiar with network simulation techniques.
To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form https://form.asana.com/?d=57018692298241&k=5MqR40fZd7jlxVUh5J-UeA. No response will be provided to inquiries unrelated to job posting compliance.
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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关于团队
Workload Networking 团队负责我们最大规模训练作业中使用的集体通信栈。我们结合使用 C++ 和 CUDA，致力于开发新型集体通信技术，以支持我们的旗舰模型在最大规模的定制超级计算机上实现高效训练。
我们训练的模型是 OpenAI 以及整个人工智能研究领域取得进展的关键要素，我们持续将整个研究部门的经验教训整合到我们的训练平台中。
关于职位
作为软件工程师（网络方向），你将设计并实现与我们训练栈紧密集成的定制网络 collective。
我们正在寻找具有底层性能关键型软件背景的人才。有 collective communication 经验者优先。
该职位位于美国加利福尼亚州旧金山。我们采用每周 3 天到办公室的混合办公模式，并为新员工提供搬迁协助。
在此职位中，你将：
- 与 ML 研究人员紧密合作，用 C++ 和 CUDA 设计并实现高效的 collective 操作。
- 确保我们最大规模的训练作业充分利用超级计算机中使用的不同网络传输方式。
- 开展仿真工作，为我们未来的超级计算机网络设计提供参考。
如果你具备以下条件，你可能适合这个职位：
- 过去曾使用 RDMA 编写过分布式算法。
- 能够熟练编写底层性能敏感的 CPU 和/或 GPU 代码。
- 熟悉网络仿真技术。
如需通知 OpenAI 你认为此职位发布存在不合规情况，请通过此表单提交报告 https://form.asana.com/?d=57018692298241&k=5MqR40fZd7jlxVUh5J-UeA。与职位发布合规性无关的询问将不予回复。
在 OpenAI，我们相信人工智能有潜力帮助人们解决巨大的全球性挑战，我们希望 AI 带来的益处能够被广泛分享。加入我们，共同塑造技术的未来。
译文仅供辅助阅读，具体要求以原始招聘来源为准。