Senior HPC Engineer, GPU Compute

About This Opportunity

Our talent team at Get A Job.ai is representing a confidential cloud infrastructure organization in their search for a Senior HPC Engineer, GPU Compute based in London. This role sits at the intersection of high-performance computing, GPU orchestration, and large-scale InfiniBand networking. You'll work on performance optimization and infrastructure development for AI and machine learning workloads at hyperscale.

Responsibilities

• Tune the performance of GPU clusters and InfiniBand networks to ensure optimal operation in HPC and GPU-based environments
• Analyze and troubleshoot the root cause of issues related to GPUs and InfiniBand networks, and propose corrective actions
• Integrate new hardware into the existing infrastructure, including support for new GPU hardware through software stacks like Kubernetes, QEMU, and KVM
• Enhance automation systems for proactive monitoring, detecting, and resolving issues in GPU and InfiniBand environments
• Configure and manage GPU devices and InfiniBand fabrics, ensuring efficient and reliable operation

What We're Looking For

Required 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)

Preferred qualifications:

• 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

Note: Coding interviews are part of our client's selection process.

How We Work With You

When you apply through Get A Job.ai, our recruiting team will review your profile and conduct an initial screening. If there's a strong match, we'll submit your candidacy to our client for consideration. Please do not attempt to contact the employer directly, as all communication is managed through our team to ensure a professional and organized process for all parties.

Pay

Compensation details will be discussed during the screening process and are competitive for the London market and this level of expertise.

Equal Opportunity: Get A Job.ai is committed to inclusive recruiting practices. We welcome applications from candidates of all backgrounds and work with clients who share our commitment to diversity and equal employment opportunity.