Machine Learning Engineer

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 Senior Machine Learning Engineer to help scale and strengthen the core infrastructure that powers real-world AI evaluation. You’ll play a foundational role in shaping how we build, deploy, and improve our model benchmarking systems, working across data pipelines, inference APIs, and new evaluation methodologies. This is an opportunity to apply your technical expertise to a platform trusted by millions, and to help define how cutting-edge AI is assessed in the wild.

As one of the first ML engineers on the team, you’ll partner closely with researchers, engineers, and product leadership to turn new ideas into reliable systems. You’ll help us move fast while staying rigorous, improving reproducibility, scaling up to new modalities, and deepening our ability to understand and compare frontier models.

• Architect and build what will become our core modeling for data and evaluation products

• Own the full stack data, model training, and eval pipelines

• Help grow a culture of feedback and rapid product iteration as we build new features as a tight-nit team

• Conduct research into state-of-the-art evaluation methods and contribute to the long-term vision for a centralized, scalable evaluation platform.

• Strong programming skills with the ability to work across the stack in a typical recommendation system or LLM stack

• Experience in deep learning, language models or reward model training

• Experience in working with LLM for fine tuning, prompt engineering, function calling etc

• Self-motivated with a willingness to take ownership of tasks

• A passion for shipping quality products

• 4+ years of industry experience or relevant projects

• Solid understanding of statistics, and various tools and methodologies for evaluating uncertainty in a way that is specific to the given product being shipped