Research Systems Engineer

We build Specific Intelligence for the enterprise: agents that continuously learn from a company's processes, data, expertise, and goals. We're building the continual learning layer and platform that captures context, memory, and decision traces across the enterprise, providing an environment where specialized agents learn how to do real work.

Why we're excited: We get to work at a rare intersection. Our product team builds the platform powering a new generation of digital coworkers. Our research team pushes the frontier of post-training and reinforcement learning to create new product experiences. Our applied research engineers sit side-by-side with customers as they ship agents into production. This combination of strong product, deep research, and boots on the ground is what we believe it takes to bring AI to the enterprise. We are product-led, research-enabled, and forward-deployed.

Our Team : We are a team of engineers, researchers, and operators. Many of us are former founders. We've built RL infrastructure at OpenAI, data foundations at Scale AI, and systems at Together, Two Sigma, Watershed, and other teams. We work with F50 customers, and we’re fortunate to be backed by Kleiner Perkins, Benchmark, Sequoia, Lux, Greenoaks, and others.

Who Thrives Here : We're looking for people who are excited about applying novel research and complex systems to real-world problems. You should be comfortable navigating unfamiliar environments quickly, whether that's a new codebase, a new customer's data architecture, or a problem domain you've never seen before. Our team genuinely enjoys working with customers: listening, empathizing, and understanding how work actually gets done in their organizations. Former founders, people who've built a lot of side projects, or anyone who's shown they can own something end-to-end, tend to do well here.

As a research systems engineer, you'll train frontier-scale models and develop the methods that make continual learning work inside enterprise environments. You'll design and run experiments at scale, explore cutting-edge RL techniques, and build the tools that let us understand what's actually happening during training. This role sits at the intersection of research and systems. You'll invent new algorithms alongside researchers, then work with infrastructure engineers to run them on GPUs.