Training: ML Framework Engineer

OpenAI•San Francisco, CA

3d•Hybrid

About The Position

As a Training: ML Framework Engineer, you will work on improving the training throughput for our internal training framework, while enabling 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. In all the projects this role pursues, the ultimate goal is to push the field forward. We’re looking for people who love optimizing performance, understanding distributed systems, and who cannot stand having bugs in their code. Since our training framework is used for large runs with massive numbers of GPUs, performance improvements here will have a large impact. 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.

Requirements

Have run small scale ML experiments
Love figuring out how systems work and continuously come up with ideas for how to make them faster while minimizing complexity and maintenance burden
Have strong software engineering skills and are proficient in Python

Responsibilities

Apply the latest techniques in our internal training framework to achieve impressive hardware efficiency for our training runs
Profile and optimize our training framework
Work with researchers to enable them to develop the next generation of models