Senior GPU Systems Architect for High-Performance AI Fabric

Bitdeer (NASDAQ: BTDR); San Jose (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Bitdeer is seeking a Senior GPU Systems & Fabric Engineer to bridge hardware and Kubernetes abstractions for AI-native cloud computing. You will design a scalable fabric layer, optimize GPU interconnects, and enable multi-tenant workloads across data centers.

Role requires deep Linux kernel knowledge, CUDA/NCCL expertise, and containerized environments, with mentoring duties and cross-team collaboration to improve reliability and performance.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field.
• 5+ years of systems engineering experience with 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.
• Experience operating, debugging, and scaling bare-metal systems in large-scale production or HPC environments.
• Familiarity with Terraform, Ansible, and CI/CD pipelines for hardware lifecycles.
• Strong problem-solving and cross-team collaboration skills.
• Experience in high-velocity, high-growth engineering environments preferred.

Responsibilities

• Architect and maintain integrations for GPU device plugins and Kubernetes Operators to expose hardware capabilities to the control plane.
• Configure and optimize high-performance host networking stacks, including RDMA, SR-IOV, RoCEv2, and InfiniBand, ensuring line-rate throughput for distributed AI training.
• Build and manage automated hardware remediation pipelines using DCGM telemetry to proactively identify, isolate, and reset degraded GPU/NIC components before they impact production jobs.
• Implement and manage sophisticated GPU slicing technologies (MIG, vGPU) to enable efficient multi-tenant inference workloads and maximize cluster utilization.
• Profile and tune kernel-level parameters, device drivers, and runtime libraries (CUDA, NCCL) to resolve bottlenecks and optimize containerized AI workloads.
• Collaborate with the Scheduling and Storage engineering teams to ensure topology-aware placement and efficient data movement across the fabric.
• Define and enforce operational standards for bare-metal provisioning, BIOS/firmware updates, and OS hardening within the containerized environment.
• Lead technical investigations into complex performance issues spanning hardware, fabric, and software, providing actionable architectural insights.
• Mentor team members and drive documentation standards for our evolving AI hardware stack.

Skills

Linux kernel internals

C

Go

System-level debugging

HPC concepts

Education

Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field

Tools

NVIDIA H100/A100 GPUs

CUDA

NCCL

RDMA/InfiniBand networks

Kubernetes device plugin architecture

Job description

Bitdeer is seeking a Senior GPU Systems & Fabric Engineer to bridge hardware and Kubernetes abstractions for AI-native cloud computing. You will design a scalable fabric layer, optimize GPU interconnects, and enable multi-tenant workloads across data centers.

Role requires deep Linux kernel knowledge, CUDA/NCCL expertise, and containerized environments, with mentoring duties and cross-team collaboration to improve reliability and performance.