OpenAI는 데이터 인프라 팀에서 차세대 학습 스택을 위한 데이터셋 인프라를 설계하고 구현할 엔지니어를 찾습니다. 분산 시스템 및 데이터 파이프라인 설계 경험이 필수이며, 수천 개의 GPU 환경에서 데이터 로딩 성능을 최적화하고 표준화된 API를 구축하는 핵심 역할을 수행합니다. 확장성과 신뢰성을 갖춘 인프라 구축에 열정이 있는 분을 환영합니다.
The Workload team is responsible for designing and running OpenAI’s LLM training and inference infrastructure that powers frontier models at massive scale. Our systems unify how researchers train and serve models, abstracting away the complexity of performance, parallelism, and execution across vast GPU/accelerator fleets. By providing this foundation, the Workload team ensures that researchers can focus on advancing model capabilities while we handle the scale, efficiency, and reliability required to bring those models to life.
We are looking for an engineer to design and implement the dataset infrastructure that powers OpenAI’s next-generation training stack. You will be responsible for building standardized dataset interfaces, scaling pipelines across thousands of GPUs, and proactively testing performance bottlenecks. In this role, you will collaborate closely with the multimodal researchers, and other infra groups to ensure datasets are unified, efficient, and easy to consume.
Design and maintain standardized dataset APIs, including for multimodal (MM) data that cannot fit in memory.
Build proactive testing and scale validation pipelines for dataset loading at GPU scale.
Collaborate with teammates to integrate datasets seamlessly into training and inference pipelines, ensuring smooth adoption and a great user experience.
Document and maintain dataset interfaces so they are discoverable, consistent, and easy for other teams to adopt.
Establish safeguards and validation systems to ensure datasets remain reproducible and unchanged once standardized.
Debug and resolve performance bottlenecks in distributed dataset loading (e.g., straggler systems slowing global training).
Provide visualization and inspection tools to surface errors, bugs, or bottlenecks in datasets.
Have strong engineering fundamentals with experience in distributed systems, data pipelines, or infrastructure.
Have experience building APIs, modular code, and scalable abstractions, while recognizing that abstractions ultimately serve the users and UX is an important part of the abstractions design.
Are comfortable debugging bottlenecks across large fleets of machines.
Take pride in building infrastructure that “just works,” and find joy in being the guardian of reliability and scale.
Are collaborative, humble, and excited to own a foundational (if not glamorous) part of the ML stack.
Have background knowledge in data math, probability, or distributed data theory.
Have worked with GPU-scale distributed systems or dataset scaling for real-time data
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.
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