Senior AI Scheduling & HPC Orchestration Architect

Bitdeer; Singapore; On-site; SGD 180,000 - 240,000; Full time

Job summary

Bitdeer in Singapore is seeking a senior distributed systems engineer to design and optimize its Kubernetes-based scheduling stack for multi-node AI workloads and HPC environments. You will lead the orchestration of GPU resources and work with storage teams to support production-scale workloads.

We value 6+ years of experience, strong communication, and hands-on expertise with PyTorch, MPI, Terraform, and Terraform-driven automation. Join us to shape the future of AI cloud services.

Qualifications

• 6+ years of distributed systems engineering experience.

Responsibilities

• Design and implement advanced batch scheduling architectures using Kubernetes-based frameworks to support multi-node scheduling.
• Develop cluster-wide admission control and queueing mechanisms to manage high-volume AI workloads.
• Leverage DRA and custom scheduler plugins to efficiently allocate GPU resources.
• Architect topology-aware pod placement for low-latency communication across NVLink/InfiniBand fabrics.
• Implement automated GPU sharing technologies and multi-tenancy isolation policies.
• Collaborate with GPU Systems and Storage teams to ensure tight integration with bare-metal hardware and storage I/O.
• Drive reliability and scalability of the scheduling stack, resolving contention and deadlocks in HPC.
• Mentor junior engineers and conduct design reviews to maintain architectural excellence.

Skills

Kubernetes scheduling

Distributed systems engineering

AI workload patterns

GPU/ HPC orchestration

Terraform

Go-based Operators

PyTorch

MPI

Education

Bachelor’s or Master’s in CS/EE

Tools

Kubernetes

Terraform

Go

PyTorch

MPI

Ray

Job description

Bitdeer in Singapore is seeking a senior distributed systems engineer to design and optimize its Kubernetes-based scheduling stack for multi-node AI workloads and HPC environments. You will lead the orchestration of GPU resources and work with storage teams to support production-scale workloads.

We value 6+ years of experience, strong communication, and hands-on expertise with PyTorch, MPI, Terraform, and Terraform-driven automation. Join us to shape the future of AI cloud services.