[Hiring] Senior Systems Software Engineer, GPU Compute @Nebius

Role Description

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.

• 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.

Qualifications

• 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).

Requirements

• 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.

Benefits

• Competitive compensation ranging from $170k-$300k + equity based on your experience.
• Career growth and learning opportunities.
• Flexibility and work-life balance.
• Collaborative and innovative culture.
• Opportunity to work on impactful AI projects.
• International environment and talented teams.