Technical Lead Manager - Training Runtime, Data(set) Movement

OpenAI; United States; Remote; USD 180,000 - 240,000; Full time

Job summary

OpenAI is seeking a deeply hands-on Technical Lead Manager to own datasets throughout our training infrastructure. You will set direction for how training jobs read data, APIs, storage contracts, versioning models, benchmarks, debugging tools, and reliability guarantees for data access across frameworks.

You will begin as the primary technical owner for dataset reads, align researchers and teams around a durable platform, and scale to broader data movement responsibilities over time.

Qualifications

• Experience building dataset read platforms for large-scale training systems.
• Strong understanding of APIs, storage formats, registration/versioning and migration paths.
• Ability to build reliable read paths with stateful iteration, caching, fast restart and recovery.
• Comfort working across Python and lower-level systems (Rust/C++).
• Experience with multimodal or RL data pipelines is a plus.

Responsibilities

• Design and build a unified dataset read platform for multiple training frameworks.
• Define dataset APIs, storage-format expectations, registration/versioning, and migration paths.
• Build reliable read paths with stateful iteration, caching, fast restart, and operational contracts.
• Create terminal and web visualizers to inspect data late in the pipeline.
• Write and review production code in data loading, service, caching, and reliability paths.
• Collaborate with teams on training frameworks, reinforcement learning, multimodal models, storage, runtime, and cluster infra.

Skills

Python

Distributed systems

API design

Data loading infra

Tools

Rust

C++

Job description

About the Team

Training Runtime builds the distributed systems that power OpenAI's largest model training runs - most recently GPT-5.5! The Data Movement area owns the infrastructure that keeps training jobs supplied with the right data at the right time, and keeps model state moving safely and efficiently across large clusters.

Our work spans machine learning systems, distributed storage, high-throughput data loading, reliability engineering, and developer experience. Success means researchers can move quickly while training runs remain fast, reproducible, debuggable, and resilient at scale.

About the Role

We are looking for a deeply hands-on Technical Lead Manager to own datasets throughout our training infrastructure. This person will set the direction for how training jobs read data: the APIs, storage contracts, versioning model, benchmarks, debugging tools, and reliability guarantees that make data access consistent across current and future training frameworks.

You will begin as the primary technical owner for dataset reads, working directly in the code while aligning researchers, training framework owners, storage teams, and infrastructure partners around a durable platform. The problem is deceptively hard at frontier scale: make enormous, heterogeneous datasets easy to consume, correct across distributed workers, observable when something goes wrong, and flexible enough to support pretraining, reinforcement learning, and multimodal training.

In this role, you will

• 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, where bugs are most visible.

• 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.

Over Time

The long‑term goal is a team that owns fast, correct, scalable, and reliable in‑cluster data movement for training: data that comes in, data that goes out, and data that moves around inside the cluster. After ramping on datasets, this role will expand to TLM ownership for broader data movement systems, including checkpoint loads/saves and snapshot transfers, while partnering closely with existing technical leads and adjacent infrastructure teams.

You might thrive in this role if you:

• 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, ensuring a reliable and efficient experience for researchers.

About OpenAI

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.

We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.

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