Staff Software Engineer, AI Data Platform

Labelbox is the RL data factory for advancing frontier agent capabilities. We build the data, evaluations, and infrastructure that frontier labs use to train and judge their agents. We're looking for talented, experienced engineers to join us. The bar is high: engineers who have strong judgment and set technical direction, quickly build prototypes that scale into the reliable systems, and are at the frontier of agent-first engineering practices and innovating to accelerate the speed of the business.

Eval systems that run millions of agent trajectories to measure model and product quality.

Fine-tuning pipelines that turn evaluation signals into measurable agent improvements.

Agent-first product surfaces: UX and infrastructure for workflows where the user is a model or an agent operator.

The systems behind hundreds of thousands of AI interviews used to source and match freelance workers to projects.

Infrastructure that scales to the throughput frontier labs actually need.

Integration of the latest models and capabilities into production within days of release.

4+ year track record of shipping systems customers and other engineers rely on

You build full stack prototypes fast and they hold up. The v1 you ship becomes the foundation the rest of the team builds on.

Strong system and API design judgement

Hard architecture and product calls land with you. You make them, defend them under pressure, and update fast when someone else is right.

You ship production code with coding agents daily. You know where they break and what it takes to make them reliable to further accelerate the team's velocity.

You set direction by being the example. Other engineers reach for your designs and your code as the reference.

You move fast in ambiguous, startup-pace environments with influence over authority.

You have worked in all parts of the stack

Deep proficiency in TypeScript and/or Python.

Production experience building LLM- or agent-driven products.

Designing evaluations for LLMs and agents, or producing high-quality data for ML systems.

Background in production distributed systems, ML infrastructure, or data systems at scale.

Our engineering team works with a modern tech stack designed for scalability, performance, and developer efficiency:

Frontend: React.js with Redux, TypeScript

Backend: Node.js, TypeScript, Python, some Java & Kotlin

APIs: GraphQL

Cloud & Infrastructure: Google Cloud Platform (GCP), Kubernetes

Databases: MySQL, Spanner, PostgreSQL

Queueing / Streaming: Kafka, PubSub

Labelbox strives to ensure pay parity across the organization and discuss compensation transparently. The expected annual base salary range for United States-based candidates is below. This range is not inclusive of any potential equity packages or additional benefits. Exact compensation varies based on a variety of factors, including skills and competencies, experience, and geographical location.

Environment: Fast-paced and high-intensity, perfect for ambitious individuals who thrive on ownership and quick decision-making

Growth: Career advancement opportunities directly tied to your impact

Vision: Be part of building the foundation for humanity's most transformative technology

We believe data will remain crucial in achieving artificial general intelligence. As AI models become more sophisticated, the need for high-quality, specialized training data will only grow. Join us in developing new products and services that enable the next generation of AI breakthroughs.

Labelbox is backed by leading investors including SoftBank, Andreessen Horowitz, B Capital, Gradient Ventures, Databricks Ventures, and Kleiner Perkins. Our customers include Fortune 500 enterprises and leading AI labs.

Your Personal Data Privacy: Any personal information you provide Labelbox as a part of your application will be processed in accordance with Labelbox’s Job Applicant Privacy notice.

Any emails from Labelbox team members will originate from a @labelbox.com email address. If you encounter anything that raises suspicions during your interactions, we encourage you to exercise caution and suspend or discontinue communications.