Research Scientist/ Research Engineer
This Research Scientist / Research Engineer role focuses on real-world impact by building frontier innovation around efficiency, gradient-free exploration, real-time learning, and interface design. Responsibilities include innovating on product algorithms, optimizing across the full ML stack, and measuring impact through real-world interactions with algorithms.
This is a research role which is focused on real world impact. We care about building our frontier innovation around efficiency, gradient free exploration, real time learning and interface design. A revolution is underway where the cost of generating synthetic data is now low enough that we can treat the data space as malleable and something which can be optimized. We can steer synthetic data towards desirable properties and make previously invisible worlds with limited data coverage more visible. The most intelligent system will increasingly be defined by building an algorithm that can interact with the world. This means for the first time researchers who care about intelligence need also be obsessed with how a model interacts. If any of these statements resonate with you, we would like to hear from you.
Above all, we're looking for great teammates who make work feel lighter and aren't afraid to go out on a limb with bold ideas. You don't need to be perfect, but you do need to be adaptable. We encourage you to apply, even if you don't check every box.
Sweat the details. Technical excellence requires obsessing over every detail. We co-design serving, algorithms, and interface as one system to maximize efficiency and enable real-time adaptation.
Move with conviction. Extraordinary results require extraordinary effort. We operate with urgency as a unified team, concentrating resources on a few high-conviction bets where research and impact intersect.
Metrics that matter. The most intelligent system will increasingly be defined by building an algorithm that can interact with the world. Research ideas are tested through working products. If it doesn't improve what users can do, we question whether it matters. We share what moves the field; we don't optimize for paper count.
Posted June 12, 2026