Senior Software Engineer, Data Infrastructure

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.

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.