Senior Software Engineer, AI Infrastructure

Persons in these roles are expected to work from our offices in Seattle. On-site requirements vary based on position and team. If you have questions about on-site work arrangements for this role, please ask your recruiter. Our  base salary range is $126,000 - $189,000, and in addition we have generous bonus plans to provide a competitive compensation package.  Who You Are: You are an expert systems engineer who occupies the space between high-level software orchestration and low-level system performance. You are motivated by the idea that world-class infrastructure should be a catalyst for public good, not a proprietary secret. You are as comfortable designing a resource allocation algorithm in Go as you are debugging a NCCL timeout. You lead by example, blending the rigor of a  Senior Software Engineer with the pragmatic, hands-on urgency of an HPC operator. Not only do you build systems, but you also ensure they thrive under the pressure of training world-class AI models. Who We Are:  While much of the AI industry has moved behind closed APIs, proprietary datasets, and "black box" infrastructure, Ai2 remains a lighthouse for Open Science. Founded by the late Paul Allen, we are a non-profit research institute dedicated to building AI for the common good. We don't have a stock price to defend or a walled garden to protect. Instead, we have a mission: to provide the global research community with the transparent, high-performance foundations they need to achieve humanity-enriching breakthroughs. What Makes Us Different: Radical Transparency: We don't just release model weights; we release the data, the training code, and the infrastructure insights. We believe the "how" is just as important as the "what." Mission over Margin: Our "bottom line" is scientific impact. This gives us the unique freedom to prioritize technical elegance, long-term stability, and open-source contributions over quarterly profit targets. The Best of Both Worlds: We operate at the pace and scale of a world-class tech startup but with the intellectual soul of a research lab. The Beaker Ecosystem: We build and operate systems like Beaker to coordinate the simultaneous training of frontier models (like OLMo) across massive GPU clusters. Our job is to ensure that the next great AI breakthrough isn't stalled by a resource bottleneck or a proprietary gatekeeper. Your Next Challenge: At Ai2, we believe that the most important AI breakthroughs should be transparent and accessible. Your challenge is to build the infrastructure that makes this possible. You will bridge the gap between our researchers and our GPU clusters. You will be a senior technical contributor responsible for ensuring that when a researcher submits a job, the software schedules it intelligently and the hardware executes it flawlessly. This involves: Designing for Scale: Designing and scaling our orchestration layer to ensure that the highest value workloads receive GPU time. Operational Excellence: Moving our HPC operations from manual intervention to high-level automation. Performance Engineering: Working directly with researchers to squeeze every bit of performance out of our GPU-accelerated computing environment. Your Responsibilities: Full-Stack Ownership: Independently design and deliver critical systems that span the entire stack—from the Beaker job scheduler to the execution runtime. System Automation: Build innovative tooling and software-defined infrastructure to accelerate researcher velocity and automate cluster health management. Performance Optimization: Conduct root-cause analysis on complex distributed system failures and implement optimizations for distributed workloads. Technical Input & Ownership: Provide valuable input into the roadmap for managing large-scale HPC systems, including the deployment of compute, networking, and storage in partnership with leadership. Mentorship & Culture: Foster a high-performance culture by reviewing code/design docs, mentoring team members, and driving process improvements within the team. Collaboration: Effectively communicate and collaborate with internal research staff to share system designs, gather feedback, and support engineers on implementation tasks. What You’ll Need: 8+ years of professional experience developing business-critical software and operating large-scale compute infrastructure. Proficiency in Go and/or Python preferred. Bachelor’s degree in related field; relevant advanced degree may substitute for equivalent years of technical work experience. Linux Expertise: Expert-level knowledge of Linux internals, and container runtimes like Docker. Distributed Systems Expertise: A proven track record of designing, debugging, and optimizing high-scale distributed systems and databases. Communication: Exceptional writing skills and the ability to drive consensus across diverse groups of researchers and engineers. A principled approach to engineering: You c