# Software Engineer, Data Infrastructure - Research

**Company:** [OpenAI](https://hotfix.jobs/companies/openai)
**Location:** San Francisco, CA
**Role:** Data Engineering
**Salary:** $250k – $380k/yr
**Skills:** Distributed Systems, Data Pipelines, APIs, GPU, PyTorch, Kubernetes, Python, Rust, Scalable Abstractions, Dataset Loading
**Posted:** 2025-09-18

> Designs and implements dataset infrastructure for OpenAI's large-scale LLM training stack, including standardized APIs for multimodal data, scaling pipelines across GPU fleets, and performance debugging. Requires strong distributed systems experience and collaboration with researchers.

## Job Description

## Responsibilities
- 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.

## Requirements
- Strong engineering fundamentals with experience in distributed systems, data pipelines, or infrastructure.
- 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.
- 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.
- Collaborative, humble, and excited to own a foundational (if not glamorous) part of the ML stack.

## Nice-to-Haves
- Background knowledge in data math, probability, or distributed data theory.
- Worked with GPU-scale distributed systems or dataset scaling for real-time data.

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**Apply:** https://hotfix.jobs/jobs/c7766506-4120-420e-b7ac-08ad093646dc
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