Senior Software Engineer, GPU Cluster Infrastructure

📋 Job Overview

FAR.AI is a non-profit AI research institute working to ensure advanced AI is safe and beneficial for everyone. Our mission is to facilitate breakthrough AI safety research, advance global understanding of AI risks and solutions, and foster a coordinated global response. We are seeking a Senior Software Engineer to join our GPU Cluster Infrastructure team.

🏢 About FAR.AI

FAR.AI is a non-profit AI research institute working to ensure advanced AI is safe and beneficial for everyone. Our mission is to facilitate breakthrough AI safety research, advance global understanding of AI risks and solutions, and foster a coordinated global response. We’re structured to support that work from early research through real-world adoption:

• Independent by design. We can pursue what's most impactful based on our theory of change and share what we find publicly.
• A portfolio approach. Rather than focus on one single direction, we run diverse bets across the safety stack. We take promising ideas from initial experiments to deployment, informed by red-team partnerships with frontier labs and governments.
• Serious infrastructure for ambitious research. A dedicated engineering team runs our compute cluster and experiment-scaling stack, so researchers spend their time on research instead of on infra.
• Setting the standard. Our events convene key decision makers; our red-team works with frontier developers and governments; and our communications inform the public. Together, this drives adoption and sets the new standard in safety.

Since our founding in July 2022, we've grown to 50+ staff, published 40+ academic papers, and convened leading AI safety events. Our work is recognized globally, with publications at premier venues such as NeurIPS, ICML including a Best Paper Honorable Mention in 2026, and ICLR, and features in the Financial Times, Nature News, Wired Magazine and MIT Technology Review. We conduct pre-deployment testing on behalf of frontier developers such as OpenAI and independent evaluations for governments including the EU AI Office and publish the AI Security Leaderboard based on our red-teaming expertise. We help steer and grow the AI safety field through developing research roadmaps with renowned researchers such as Yoshua Bengio; running FAR.Labs, an AI safety-focused co-working space in Berkeley housing 40+ members; and supporting the community through targeted grants to technical researchers.

🎯 The Role

Foundations is FAR.AI's infrastructure and engineering team. Our remit is broad: we run the compute platform, build the tools and frameworks researchers work in, automate research workflows, and help teams scale experiments well past what they'd manage alone. Our job is to accelerate the research. We do so by working directly with researchers through embedded engagements and day-to-day consulting, and building systems that can scale with the organization as it grows.

Foundations is growing quickly, and our infrastructure portfolio is growing fastest. We run FAR.AI's research on a mix of bare-metal and managed Kubernetes GPU clusters from multiple providers. We rent the hardware and operate the platform ourselves. The fleet has grown from dozens to hundreds of GPUs this year and it's continuing to grow quickly: we're adding providers, taking on users beyond our own researchers, and moving experiments onto frontier open-weight models. A large amount of research is now being done by AI agents working directly on the cluster, which is driving updates to our platform infrastructure and security.

Running it well now takes dedicated specialists, so we're standing up an infrastructure sub-team that owns the cluster fleet: adding capacity, designing and managing the networking and storage under it, infrastructure as code, and the security posture, plus some of the platform layer above it. It works directly with research teams as their needs change.

✅ Key Responsibilities

• Operate the Kubernetes GPU fleet day to day. You handle node lifecycle, upgrades, driver and image rollouts, staged changes with safe rollback, and capacity planning.
• Own batch scheduling and multi-tenancy, including queues, quotas, priorities, preemption, gang scheduling, and fair share across research teams.
• Design and run the storage under the fleet, from high-performance shared filesystems for datasets and checkpoints to object storage tiers, quotas, and backups.
• Keep multi-node training runs fault-tolerant. You own node health and automated draining, debug NCCL and fabric problems, track down stragglers and flaky GPUs, and build the checkpoint and restart patterns.
• Harden the platform, covering identity and access, network policy, secrets, workload isolation, and sandboxing for the AI agents that run on the cluster.
• Bring new capacity online. You acceptance-test providers on fabric, NCCL, and storage throughput, hold them to their SLAs, and integrate new clusters into the platform with infrastructure as code.
• Work directly with research teams on their infrastructure problems and turn the recurring ones into platform fixes. Share the on-call rotation, run

🎁 Benefits

Compensation is based on structure and experience using an annualized salary of $150K – $275K. Work-related travel and equipment expenses are covered. In-person staff receive catered lunch and dinner at our Berkeley office.