Senior GPU Systems & Fabric Engineer

Bitdeer; San Jose (CA); On-site; USD 140,000 - 210,000; Full time

Job summary

Bitdeer seeks a Senior GPU Systems & Fabric Engineer to bridge hardware and the Kubernetes layer, building scalable, multi-tenant AI cloud primitives. You will optimize GPU/NIC hardware, fabric transport, and software stacks to support low-latency AI workloads.

You will design and implement device plugins, MIG/vGPU strategies, and transport networks, shaping the foundation for AI-native cloud computing across data centers.

Qualifications

• 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.
• Proven track record of operating, debugging, and scaling bare-metal systems in large-scale production or HPC environments.
• Familiarity with infrastructure automation (Terraform, Ansible, CI/CD) for hardware lifecycles.
• Strong problem-solving skills and excellent cross-team communication.

Responsibilities

• Architect and maintain integrations for NVIDIA/AMD GPU device plugins and Kubernetes Operators.
• Configure and optimize high-performance host networking stacks (RDMA, SR-IOV, RoCEv2, InfiniBand).
• Build and manage automated hardware remediation pipelines using DCGM telemetry.
• Implement and manage GPU slicing technologies (MIG, vGPU) for multi-tenant workloads.
• Profile and tune kernel parameters, drivers, and CUDA/NCCL runtimes.
• Collaborate on topology-aware placement and data movement across the fabric.
• Define and enforce bare-metal provisioning and OS hardening standards.
• Lead investigations into performance issues across hardware and software.
• Mentor team members and drive documentation for AI hardware stack.

Skills

Linux kernel

C

Go

GPU architectures

CUDA

NCCL

Kubernetes

RDMA

InfiniBand

Device plugins

Terraform

Ansible

CI/CD

Problem solving

Communication

Education

Bachelors or Masters in CS/EE

Tools

CUDA

NCCL

RDMA

InfiniBand

Kubernetes

Terraform

Ansible

CI/CD pipelines

Job description

Bitdeer is a world-leading technology company for AI and Bitcoin mining infrastructure.

Bitdeer is committed to providing comprehensive Bitcoin mining solutions for its customers and building AI computational infrastructure to support the AI revolution. Bitdeer handles complex processes involved in computing such as equipment procurement, transport logistics, data center design and construction, equipment management, and daily operations. Bitdeer also offers advanced cloud capabilities to customers with high demand for artificial intelligence.

Headquartered in Singapore, Bitdeer has deployed data centers across multiple countries, including the United States, Norway, Bhutan, and Ethiopia.
To learn more, visit https://ir.bitdeer.com/

Position Overview

We are seeking a Senior GPU Systems & Fabric Engineer to serve as the critical bridge between our physical GPU/network infrastructure and the Kubernetes abstraction layer. You will be responsible for creating the high-performance 'hardware foundation' that makes AI-native cloud computing possible. This role requires deep expertise in Linux kernel internals, GPU architectures, and high-speed interconnects, as you will be tasked with transforming raw, bare-metal compute resources into scalable, resilient, and multi-tenant cloud primitives. You will drive the design of our fabric layer, ensuring that our AI workloads have the low-latency, high-bandwidth environment they require to perform at industry-leading speeds.

Key Responsibilities

• Architect and maintain integrations for NVIDIA/AMD 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.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field.
• 5+ years of systems engineering experience, with 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 (e.g., Terraform, Ansible, CI/CD pipelines) for managing hardware lifecycles.
• Strong problem-solving skills, with the ability to navigate ambiguous performance challenges at the intersection of hardware and software.
• Excellent communication skills, with a collaborative approach to working across infrastructure, scheduling, and reliability teams.
• Experience working in high-velocity, high-growth engineering environments is strongly preferred

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Bitdeer is committed to providing equal employment opportunities in accordance with country, state, and local laws. Bitdeer does not discriminate against employees or applicants based on conditions such as race, color, gender identity and/or expression, sexual orientation, marital and/or parental status, religion, political opinion, nationality, ethnic background or social origin, social status, disability, age, indigenous status, and union.