Senior Systems Software Engineer, GPU Compute

The role

We’re looking for a Senior Software Systems Engineer to join our team and play a key role in the development of our cutting-edge hyperscaler platform. The GPU & InfiniBand team is responsible for enhancing and optimizing the core components of our Cloud platform, with a specific focus on GPU computing, InfiniBand networks, and the KVM/QEMU stack. You’ll work closely with hardware virtualization and device emulation technologies, ensuring high performance and security in multi-GPU, HPC environments.

The role involves analyzing, troubleshooting, and improving infrastructure to support new hardware, fine-tuning system performance, and automating fault detection and resolution in a complex system.

In this position, you will be responsible for:

• Tuning the performance of GPU clusters and InfiniBand networks to ensure optimal operation in HPC and GPU-based environments.
• Analyzing and troubleshooting the root cause of issues related to GPUs and InfiniBand networks, and proposing corrective actions.
• Integrating new hardware into the existing infrastructure, including support for new GPU hardware through software stacks like Kubernetes, QEMU, and KVM.
• Enhancing automation systems for proactive monitoring, detecting, and resolving issues in GPU and InfiniBand environments.
• Configuring and managing GPU devices and InfiniBand fabrics, ensuring efficient and reliable operation.

We expect you to have:

• 5+ years of professional experience in system-level software development (focused on performance optimization, low-level programming).
• 3+ years of hands-on experience with Linux systems (administration, troubleshooting, and performance tuning).
• In-depth understanding of server architecture, including PCIe devices, NICs, Linux OS/Kernel, and high-performance computing (HPC) systems.
• Strong proficiency in one or more performance-oriented programming languages (C/C++, Go, Python).

It would be a plus if you have:

• Experience with GPU end-to-end testing in a cluster environment using InfiniBand networking.
• Proven track record of analyzing and optimizing the performance of HPC workloads (e.g., simulations, data analysis, AI/ML workloads).
• Familiarity with RDMA, RoCE, and InfiniBand protocols for high-performance communication.
• Background in Software-Defined Networking (SDN) and experience with HPC cluster networking.
• Understanding of QEMU/KVM virtualization and managing virtualized environments.
• Experience with deep learning frameworks such as PyTorch and TensorFlow, and their integration with HPC systems.
• Familiarity with collective communication libraries like MPI and NCCL for distributed computing.

We offer competitive salaries ranging from $170k-$300k + equity based on your experience.

We conduct coding interviews as part of the process.

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Benefits & Perks:

• Competitive compensation
• Career growth and learning opportunities
• Flexibility and ownership
• Collaborative and innovative culture
• Opportunity to work on impactful AI projects
• International environment and talented teams

Equal Opportunity Statement:

Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.