Senior Software Engineer, ML 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 Senior Software Engineer (ML 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.