Senior GPU Systems & Fabric Engineer

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

Bitdeer is committed to providing comprehensive Bitcoin mining solutions for its customers. Apart from designing industry-leading ASIC chips and manufacturing mining rigs, the Group handles complex processes involved in computing across the value chain. This includes equipment procurement, transport logistics, datacenter design and construction, equipment management, and network and facility operations. Bitdeer also offers advanced cloud capabilities to customers with a high demand for artificial intelligence.

Headquartered in Singapore, Bitdeer operates globally with a diversified 3 GW energy portfolio, and deploys Bitcoin mining and HPC datacenters in the United States, Bhutan, Norway, Canada, Malaysia, and Ethiopia.

• →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.

• →A culture that values authenticity and diversity of thoughts and backgrounds;
• →An inclusive and respectable environment with open workspaces and exciting start-up spirit;
• →Fast-growing company with the chance to network with industrial pioneers and enthusiasts;
• →Ability to contribute directly and make an impact on the future of the digital asset industry;
• →Involvement in new projects, developing processes/systems;
• →Personal accountability, autonomy, fast growth, and learning opportunities;
• →Attractive welfare benefits and developmental opportunities such as training and mentoring.

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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, colour, 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.

#LI-ST1

• 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.