Arena operates a community-driven AI evaluation platform where millions of users test frontier models and generate ground-truth performance signals. The tech stack—Python, PyTorch, Next.js, PostgreSQL, Apache Airflow—reveals an ML-native backend paired with a modern web frontend, built to handle billions of requests. Active projects span open-source dataset releases, real-time data pipelines, and platform security, while hiring is heavily weighted toward senior engineers and researchers, indicating rapid scaling of both infrastructure and research capabilities.
Arena is a community platform founded by UC Berkeley researchers that aggregates real-world AI model performance through direct user feedback. The company operates a public leaderboard grounded in builder, researcher, and creator interactions with frontier AI models. Infrastructure priorities include handling billions of requests, scaling low-latency event pipelines, and building analytical layers on top of evaluation signals. The organization is based in San Francisco and actively hiring across engineering, data, research, and go-to-market functions.
Python, PyTorch, NumPy, Pandas, Apache Spark for ML and data processing; PostgreSQL for persistence; Next.js and Tailwind CSS for frontend; Apache Airflow for orchestration; Cloudflare for infrastructure; Okta for identity; Salesforce for operations.
Open-source dataset releases, real-time data and API infrastructure, low-latency event pipelines, analytics-layer data models, platform security features, and evaluation signal surface development. Infrastructure scaling for billions of requests is a core focus.
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