Senior GPU Systems – Fabric Engineer

🔥 0 minutes ago

🏄 California, Texas – Remote

🏄 California – Remote 🤠 Texas – Remote

⏰ Full Time

🟠 Senior

👷🏻‍♀️ Engineer

👻 Ghost score 10%

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Bitdeer Group

WebsiteLinkedInAll Job Openings

201 - 500 employees

💼 Consulting

📦 Logistics

🏗️ Construction

💰 Post-IPO Equity on 2023-05

Consulting • Logistics • Construction

Bitdeer Group is a leader in the blockchain and high-performance computing industry. It is one of the world’s largest holders and suppliers of hash rate, offering specialized mining infrastructure and high-quality hash rate sharing products. Founded by cryptocurrency pioneer Jihan Wu and led by CEO Matt Linghui Kong, the company is headquartered in Singapore with mining datacenters in the United States, Norway, and Bhutan. Bitdeer is committed to providing comprehensive computing solutions, including cloud services and AI capabilities, while emphasizing dedication, authenticity, and trustworthiness in its mission to be the most reliable provider in the industry.

📋 Description

• Architect and maintain NVIDIA/AMD GPU device plugin and Kubernetes Operator integrations • Configure and optimize RDMA, SR-IOV, RoCEv2, and InfiniBand host networking for distributed AI training • Build automated hardware remediation pipelines using DCGM telemetry • Implement and manage GPU slicing technologies including MIG and vGPU for multi-tenant inference • Profile and tune kernel parameters, device drivers, and CUDA/NCCL runtime libraries • Collaborate with Scheduling and Storage engineering teams on topology-aware placement and data movement • Define operational standards for bare-metal provisioning, BIOS/firmware updates, and OS hardening • Lead investigations into hardware, fabric, and software performance issues • Mentor team members and drive documentation standards for the AI hardware stack

🎯 Requirements

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field • 5+ years of systems engineering experience • Strong proficiency in Linux kernel internals, C, or Go • Hands-on experience with GPU architectures (NVIDIA H100/A100), CUDA runtimes, and distributed networking (RDMA, InfiniBand) • Deep understanding of containerized environments and Kubernetes device plugin architecture • Proven track record of operating, debugging, and scaling bare-metal systems in large-scale production or HPC environments • Familiarity with infrastructure automation such as Terraform, Ansible, and CI/CD pipelines • Strong problem-solving skills for ambiguous hardware/software performance challenges • Excellent communication skills and collaborative approach across infrastructure, scheduling, and reliability teams • Experience in high-velocity, high-growth engineering environments strongly preferred

🏖️ Benefits

• Equal employment opportunities in accordance with country, state, and local laws