$ cat jobs/product-solutions-engineer-arena-6e504cc4f444.json
Product Solutions Engineer
ABOUT ARENA INTELLIGENCE Arena is the platform for evaluating how AI models perform in the real world. Founded by researchers from UC Berkeley's SkyLab, we're on a mission to measure and advance the frontier of AI for real-world use, and to build the foundation for everyone to understand, shape, and benefit from it. Tens of millions of people use Arena each month to evaluate how frontier systems handle the work they actually do. The preferences they share power the most transparent, rigorous, and human-centered evaluations in AI. Leading AI labs, enterprises, and independent researchers rely on our work and open datasets to understand how models behave in real workflows: agentic coding, creative generation, professional productivity, and beyond. We go beyond leaderboards and decompose what human experience reveals about AI, so models advance toward the work people actually do. We're a team of researchers, academics, builders, and creatives from UC Berkeley, Google, Stanford, and DeepMind. We seek truth, move fast, and value craftsmanship, curiosity, and impact over hierarchy. We're building a company where thoughtful, curious people from all backgrounds can do their best work together, in an office culture that radiates excellence, energy, and focus. ABOUT THE ROLE This role has two core parts, both centered around working closely with the best AI labs in the world. First, you’ll partner directly with our lab customers to integrate their models, run and deliver evals, and act as their go-to person at Arena Intelligence. You’ll plug into their research roadmap, understand where they’re headed, and help them get real value from our data. Along the way, you’ll spot gaps, surface new opportunities, and help shape what we build next. Second, you’ll roll up your sleeves and build. You’ll take on specific customer engineering asks and ship solutions that push the frontier of what our platform can do. Some of what you build may eventually scale into our Data or Applied ML s