<aside> 🧠 Our mission at Surge is to build the human infrastructure to power the next generation of AI.

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We’re building a platform that powers leading AI groups, including OpenAI, Anthropic, Meta, and Google, by providing high-quality human feedback data to evaluate and train their models. Surge was founded by former ML engineers focused on furthering the state of the art in AI through close collaboration with researchers. You will work directly with scientists to understand their needs and design optimal data collection paradigms, quality controls, and experimentation techniques to generate insightful, compelling, safe, and human-aligned model improvements.

As part of a small, rapidly growing team you will embed with research and applied AI teams at companies like OpenAI, Anthropic, Meta, and Google to analyze their model performance issues and data needs. Drawing on your analytical abilities, you'll design custom data collection workflows, quality control processes, and experimentation techniques to help these teams generate performance improvements. This is a unique opportunity to use your technical skills to further cutting-edge AI innovation.

What we're looking for:

• Analytical Orientation - Interest and aptitude for analyzing model performance to determine data needs
• Scientific Curiosity - Applying latest research to create optimal data collection methods
• Customer Focus - Ensuring our platform directly enables customer model innovations

You will gain experience:

• Analyzing the latest models and identifying performance gaps
• Creating custom data collection pipelines for specific model objectives
• Implementing quality controls that reduce bias and maximize insights
• Running rigorous experiments with scientists to advance their research

To apply, please email [email protected] with your background and interest in this role. We welcome personal projects and writings!