About the role
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
Arena Intelligence is seeking a Data Infrastructure 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.
You’ll
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.
You’ll have
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.
Bonus Points
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.
What we offer
We offer competitive compensation and equity aligned to the markets where our team members are based. The base salary range will depend on the candidate’s permanent work location.
Comprehensive health and wellness benefits, including medical, dental, vision, and additional support programs.
The opportunity to work on cutting-edge AI with a small, mission-driven team
A culture that values transparency, trust, and community impact
Come help build the space where anyone can explore and help shape the future of AI.
Arena Intelligence provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity, or gender expression. We are committed to a diverse and inclusive workforce and welcome people from all backgrounds, experiences, perspectives, and abilities.
About Arena
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.
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Job details
Location
San Francisco, CA
Funding
Total raised
$250M
Last stage
Series A
Investors
Founders
What happens next.
No applications, no recruiter spam. Just the intro.
Confirm the fit
A few questions to make sure this role is the right shape for you. Two minutes.
I pitch you to the company
I write the intro, send it to the founder, and handle the back-and-forth.
A meeting lands on your calendar
If they’re a yes, I book the chat. You show up — that’s the whole job-hunt.
