Staff Software Engineer, GPU Infrastructure

1 week ago

Canada Jobgether Full time

Staff Software Engineer, GPU Infrastructure (HPC) This position is posted by Jobgether on behalf of a partner company in the United States, Canada. As a Staff Software Engineer in GPU infrastructure, you will design, build, and operate high‑performance computing clusters to accelerate AI and machine learning workloads. You will collaborate closely with researchers and engineers to ensure workloads run reliably, efficiently, and at scale across cloud environments. The role includes optimizing infrastructure for cost, performance, and stability, while providing self‑service tools for ML teams, troubleshooting complex issues, implementing automation and observability best practices, and driving innovations in distributed GPU/TPU systems. This position offers opportunities to mentor engineers, influence infrastructure strategy, and directly impact the development of cutting‑edge AI models in a fast‑paced, collaborative environment. Accountabilities Design, deploy, and manage Kubernetes‑based GPU/TPU superclusters across multiple clouds for AI/ML workloads Optimize HPC infrastructure for distributed training frameworks such as JAX, PyTorch, and TensorFlow Identify and resolve performance bottlenecks, system failures, and infrastructure issues Build self‑service tools to enable researchers to monitor, debug, and optimize AI/ML training jobs independently Implement best practices for automation, observability, and infrastructure‑as‑code (IaC) Collaborate closely with AI researchers and ML engineers to translate emerging needs into robust infrastructure solutions Mentor team members, conduct code reviews, document processes, and foster a culture of knowledge sharing Requirements Deep expertise in ML/HPC infrastructure, including GPU/TPU clusters and distributed training frameworks Proven experience with cloud‑native Kubernetes deployments at scale Strong programming skills in Python and Go, with preference for open‑source contributions Knowledge of Linux internals, RDMA networking, and performance optimization for ML workloads Demonstrated ability to collaborate with research teams and solve complex infrastructure challenges Self‑directed problem‑solving mindset with ability to drive impact in fast‑paced environments Experience in building scalable, resilient, and maintainable infrastructure systems Benefits Inclusive and collaborative work culture Opportunities to work on cutting‑edge AI research and infrastructure projects Weekly lunch stipend, in‑office meals, and snacks Comprehensive health and dental benefits, including mental health budget 100% parental leave top‑up for up to six months Personal enrichment benefits for arts, fitness, and workspace improvement Remote‑flexible work options, co‑working stipend, and offices in major global cities Six weeks of vacation (30 working days) #J-18808-Ljbffr

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