# Technical Lead Manager - Training Runtime, Data Movement

**Company:** [OpenAI](https://hotfix.jobs/companies/openai)
**Location:** San Francisco, CA
**Role:** Engineering Management
**Salary:** $295k – $445k/yr
**Experience:** 7+ years
**Skills:** Python, Rust, C++, Torch.Utils.Data, Distributed Training, Data Loading, Stateful Iterators, Checkpoint/Restart, Caching, High-Throughput Storage
**Posted:** 2026-06-08

> Hands-on Technical Lead Manager to own dataset reads and data movement infrastructure for large-scale model training at OpenAI. Sets direction for APIs, storage contracts, versioning, reliability, and debugging tools across training frameworks.

## Job Description

## Responsibilities
- Design and build a unified dataset read platform for multiple current and future training frameworks.
- Define dataset APIs, storage-format expectations, registration/versioning, and migration paths that make data access reproducible and maintainable.
- Build reliability into the read path, including stateful iteration, caching, fast restart, recovery, and clear operational contracts.
- Build terminal and web-based visualizers that let teams inspect text, multimodal, and reinforcement learning data late in the pipeline.
- Write and review production code in core data loading, service, caching, and reliability paths.
- Partner with teams working on training frameworks, reinforcement learning, multimodal models, storage, runtime, and cluster infrastructure.

## Requirements
- Have built or owned dataset, data loading, storage, or distributed training infrastructure at large scale (e.g. torch.utils.data).
- Care equally about API design, debugging ergonomics, performance, and bit-level correctness.
- Understand the failure modes of large distributed training jobs and know how data systems can create or prevent them.
- Have experience with stateful iterators, checkpoint/restart semantics, caching, remote services, or high-throughput storage reads.
- Are comfortable working across Python and lower-level systems code; Rust or C++ experience is useful but not required.
- Have worked with multimodal, video, reinforcement learning, or pretraining data pipelines where small data bugs are expensive and hard to diagnose.
- Can lead through code and technical judgment before a team exists, and can later manage engineers without losing the hands-on edge.
- Obsess over developer experience by eliminating friction, such as manual preprocessing scripts and niche cluster-specific bugs.

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