Senior Software Engineer, Data Infrastructure

Arena Intelligence is the open platform for evaluating how AI models perform in the real world. Created by researchers from UC Berkeley’s SkyLab, our mission is to measure and advance the frontier of AI for real-world use.

Millions of people use Arena Intelligence each month to explore how frontier systems perform — and we use our community’s feedback to build transparent, rigorous, and human-centered model evaluations. Leading enterprises and AI labs rely on our evaluations to understand real-world reliability, alignment, and impact. Our leaderboards are the gold standard for AI performance — trusted by leaders across the AI community and shaping the global conversation on model reliability and progress.

We’re a team of researchers, engineers, academics, and builders from places like UC Berkeley, Google, Stanford, DeepMind, and Discord. 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. Everyone on our team is a deep expert in their field — our office radiates excellence, energy, and focus.

Arena Intelligence is seeking a Software Engineer to join our team and build the data pipelines and infrastructure that powers real-world AI evaluation. You'll play a crucial role in designing and building the data pipelines that process and analyze tens of millions user vote data, directly impacting how we understand and evaluate AI model performance. This role is ideal for someone who thrives in fast-moving environments and interested in building products to ensure accurate and fair evaluation of human preferences across different models, which will shape the direction of future AI development.

As an early member of our data engineering team, you'll partner closely with researchers, engineers, and product leadership to retrieve valuable data and insights from human votes and feedback. You'll help us move fast while staying rigorous, improving data quality, scaling our infrastructure to new levels, and deepening our ability to compare frontier models and predict human preferences.

• Design and build robust data pipelines to ingest, process, and transform user vote data to features essential for model performance evaluation.

• Collaborate with researchers and product leadership to understand product goals and necessary data.

• Design and implement solutions to generate result dashboards and reports, providing useful information for the public, model providers, and researchers.

• Ensure the integrity, data quality, and reliability of the pipelines.

• Scale our data infrastructure to accommodate increasing data volumes and evolving analytical needs.

• 5+ years of experience in software engineering, with a dedicated focus on data engineering and big data technologies

• Proficiency in SQL and at least one programming language commonly used for data analysis (Python (preferred), Scala, R).

• Hands-on experience with data processing and pipeline frameworks (Apache Spark, Ray Data, etc.) and at least one popular big data analytics platform (Databricks, Snowflake).

• Demonstrated experience in designing, implementing, optimizing, and debugging production data pipelines.

• Prior work in data analytics or datalake platforms.

• Experience in advanced data analysis tools, such as Delta lake, streaming tables.

• Exposure to machine learning is a plus.