We’re building a platform that powers the biggest AI groups in the world — including OpenAI, Anthropic, Meta, and Google — with human feedback data for evaluating and training their models. Surge was founded by former ML engineers focused on providing the highest quality data in the industry. Instead of outsourcing to call centers overseas, we’ve built an elite workforce based in the US, custom annotation tools, and sophisticated quality control systems. Our product has been a “game-changer” for ML teams, and we’ve run a profitable business from day one without raising venture funding.
As a Machine Learning Research Scientist, you’ll help shape how the world’s most advanced AI models are trained, aligned, and evaluated. You’ll work on highly practical problems at the intersection of research and deployment — from designing model-in-the-loop data pipelines, to evaluating frontier LLMs, to prototyping new methods for data-centric RLHF.
You’ll collaborate closely with our internal engineering team and our partners at top AI labs, turning research ideas into systems that improve real-world model behavior. This is a role for someone who wants to move fast, stay close to production, and make research that matters.
To apply, please email [email protected] with your background and interest in collaborating with Surge. Please include the name of the role you’re applying for in the subject line or email body. We welcome personal projects and writings!