Senior Software Engineer, ML 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 Senior Software Engineer (Infrastructure) to lead the design and development of scalable, high-performance real-time data and API infrastructure. In this role, you’ll architect systems that capture and process large volumes of serving requests in real time, powering the insights that help researchers and developers build the world’s most advanced AI and its applications. Your work will be foundational to how we surface trustworthy, transparent, and timely evaluation signals across the platform. This role is ideal for someone who thrives in fast-moving environments, cares deeply about performance and reliability, and wants to build systems that help the AI community better understand what models are the best for their real-world use cases.

• Architect and scale high-performance, real-time API and data systems

• Design and implement low-latency pipelines to process and analyze large-scale event streams

• Ensure reliability through robust data integrity, availability, and consistency mechanisms

• Mentor and guide engineers on infrastructure best practices, architecture, and performance tuning

• Collaborate cross-functionally with AI researchers, product leaders, and engineers to anticipate evolving infrastructure needs and deliver resilient, extensible systems

• 5+ years of experience in software engineering, with a focus on infrastructure or large-scale data and ML systems

• Deep expertise in distributed systems, stream processing, and scalable backend architecture

• Proven ability to design and operate low-latency, high-throughput, and fault-tolerant systems

• Strong foundation in systems design, performance tuning, and building reliable, fault-tolerant services

• Comfortable in a dynamic, high-ownership, fast-growth environment

• Prior experience with PyTorch model development is a plus.