Research Scientist
Surge AI
Research Scientist
Surge AI
Delivers high-quality AI training data
Our mission is to raise AGI with the richness of human intelligence — curious, witty, imaginative, and full of unexpected brilliance.
Surge was founded by engineers and researchers who dreamed of building the next generation of AI. Our platform powers the most capable models in the world, in partnership with the AI models you use every day.
At Surge, we believe the path to AGI isn't just about scaling compute—it's about embracing the unlimited ceiling of human intelligence and creativity in the data that shapes these systems. Our platform combines elite human expertise with cutting-edge tools for scalable oversight, from building rich RL environments to conducting rigorous evaluations that go beyond benchmarks. We've run a profitable business from day one without raising venture funding.
As a Research Scientist focused on data, you’ll work at the cutting edge of LLM development by designing the datasets that shape how frontier models behave. You’ll partner directly with AI research teams to experiment with new data collection strategies, evaluate dataset quality, and uncover insights that improve alignment, safety, and model performance.
This is a research-driven, impact-heavy role: you’ll have the opportunity to test ideas quickly in live production environments, shape data-centric methodologies for some of the world’s top AI labs, and help define how high-quality data fuels the next generation of AI systems.
Deep Curiosity About Data – Obsession with understanding how the structure, quality, and selection of data influence LLM performance
Bias Toward Insight and Iteration – You think critically but move fast, designing lightweight experiments to generate actionable results
Desire to Shape AI Development – Drive to build the foundational data layer that defines how the next generation of AI systems behave
Research data collection strategies and designing high-impact data slices that uncover model failure modes
Model annotator behavior and designing experiments to optimize instruction clarity and reward signal reliability
Develop metrics and frameworks for evaluating dataset quality, diversity, and impact on downstream model alignment
Surge AI provides high-quality training and evaluation data for AI models. It creates human-annotated datasets, preference data, and reinforcement learning from human feedback (RLHF) to help developers of large language models and other machine learning systems improve accuracy, alignment, and real-world performance, especially for advanced generative AI tasks. The company targets the high end of the data labeling market by prioritizing quality, scalability, and the ability to handle complex, model-critical labeling rather than simple commodity annotations. Its goal is to support better-performing, safer, and more reliable AI systems by delivering data that directly feeds model training and evaluation.
Explore more opportunities at Surge AI