Runpod is pioneering the future of AI and machine learning, offering cutting-edge cloud infrastructure for full-stack AI applications. Founded in 2022, we are a rapidly growing, well-funded company with a remote-first organization spread globally. Our mission is to empower innovators and enterprises to unlock AI's true potential, driving technology and transforming industries. Join us as we shape the future of AI. We are building Cloud services focused on accelerating AI adoption. Whether you're an experienced ML developer training a large language model, or an enthusiast tinkering with stable diffusion, we strive to make GPU compute as seamless and affordable as possible.
Director of Infrastructure Engineering
Location
United States
Posted
1 day ago
Salary
$225K - $325K / year
Seniority
Lead
Job Description
Director of Infrastructure Engineering
Runpod
Role Description We’re looking for a Director of Infrastructure Engineering to lead and scale Runpod’s core cloud and bare-metal environments. This role owns the critical foundational layers of our platform—Site Reliability Engineering (SRE), global networking, High-Performance Computing (HPC) networks, and distributed storage engines. You’ll build the operating rhythm, culture, and technical direction that ensures Runpod remains highly available, performant, and capable of scaling to meet massive GPU computing demands. You will partner tightly with Product Engineering, Product, and GTM leadership to support enterprise customers. Your focus is ensuring that our underlying infrastructure provides the absolute fastest, most reliable, and lowest-latency path for customers training and running large-scale AI workloads. - Own Core Infrastructure & SRE: Lead multiple engineering teams responsible for Site Reliability Engineering, networking, and storage. Establish rigorous SRE practices, driving SLA/SLO definitions, incident response, observability, and automated remediation. - Architect HPC & Global Networking: Oversee the design, scaling, and operation of Runpod’s global network backbone, as well as ultra-low-latency HPC cluster networks. Drive the implementation and optimization of InfiniBand and RDMA over Converged Ethernet (RoCE) to support massive, multi-node GPU training workloads. - Drive Storage Engine Innovation: Direct the architecture and performance tuning of highly scalable, distributed storage systems. Ensure our storage engines can deliver the massive IOPS and throughput required to keep high-end GPUs fed with data during deep learning tasks. - Build a High-Output Org: Hire, mentor, and grow highly technical engineering managers and senior ICs (network architects, systems engineers, SREs). Create a culture of ownership, operational excellence, and craft in a remote-first environment. - Translate Scale into Strategy: Partner with Program Management and Product to forecast capacity requirements, shape technical roadmaps, and convert massive scale challenges into clear technical scopes, milestones, and measurable outcomes. - Continuously Improve Systems & Flow: Drive measurable improvements in infrastructure reliability and delivery metrics, such as deployment frequency, MTTR (Mean Time To Recovery), infrastructure as code (IaC) coverage, and system uptime. - Architectural Stewardship: Provide architectural oversight for bare-metal provisioning, virtualization layers, network fabrics, and storage clusters, ensuring seamless scalability without becoming a bottleneck for your teams. - Cross-Functional Partnership: Coordinate cleanly with product delivery and platform teams to ensure the infrastructure primitives they rely on are robust, well-documented, and highly available. Qualifications - 7+ years leading software, infrastructure, SRE, or networking teams, including managing managers and multiple squads, with a proven record of scaling high-availability cloud environments. - 8+ years building and operating large-scale distributed systems, bare-metal infrastructure, or public/private cloud platforms. - Proven hands-on background or strong architectural understanding of ultra-low latency networking. Deep familiarity with InfiniBand and/or RoCE, spine-leaf architectures, and global WAN routing protocols (BGP). - Experience building, operating, or tuning high-performance distributed storage systems and parallel file systems (e.g., Ceph, Lustre, Weka, NVMe-oF) capable of handling heavy AI/ML I/O loads. - Strong foundation in reliability engineering, infrastructure-as-code (Terraform, Ansible), container orchestration (Kubernetes), and modern observability stacks. - Experience building culture, accountability, and momentum across distributed technical teams. - Clear written and verbal communication, strong stakeholder management, and calm, decisive leadership during high-stakes operational incidents. - Successful completion of a background check. Requirements - Direct experience architecting and operating infrastructure specifically optimized for massive GPU clusters and AI/ML workloads. - Deep understanding of hardware architectures, GPU interconnects (NVLink), and datacenter topology. - Track record of scaling infrastructure teams in hyper-growth startup environments. - Open-source contributions or active recognition within the infrastructure, networking, or Kubernetes communities. Benefits - The competitive base pay for this position ranges from ($225,000 - $325,000). This salary range may be inclusive of several career levels at Runpod and will be narrowed during the interview process based on a number of factors, including the candidate’s experience, qualifications, and location. - Meaningful equity in a fast-growing company—everyone on the team receives stock options — your impact drives our growth, and you share in the upside. - Generous medical, dental & vision plans. - Flexible PTO - take the time you need to recharge. - Most roles are remote work first with an inclusive, collaborative teams utilizing Slack as the main form of internal communication. - $1,200 Home Office & Equipment Stipend - We set you up for success from day one with gear and support to create your ideal workspace.
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