Senior AI Scheduling Architect for GPU-Accelerated Cloud

Bitdeer Group; San Jose, Austin (CA, TX); Hybrid; USD 180,000 - 280,000; Full time

Job summary

Bitdeer Group is seeking a Staff AI Scheduling & Orchestration Engineer to lead the workload placement logic for our AI-native NeoCloud platform.

You'll tackle advanced batch scheduling, multi-node gang scheduling, and GPU-accelerated workloads, shaping a high-performance fabric across NVLink and InfiniBand. This role blends distributed systems with AI at scale and offers impact across our compute fleets.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field.
• 6+ years of distributed systems engineering, with deep, hands-on expertise in Kubernetes scheduling frameworks and orchestrators.
• Extensive experience with AI workload execution patterns and distributed training frameworks (e.g., PyTorch Distributed, Ray, MPI).
• Proven track record of operating, debugging, and scaling scheduling stacks in HPC or large-scale production cloud environments.
• Strong knowledge of GPU hardware architectures and the specific scheduling challenges related to distributed AI training and inference.
• Experience with infrastructure automation and infrastructure-as-code (e.g., Terraform, Go-based Operators).
• Excellent technical communication and leadership skills; ability to influence cross-functional teams and align architectural goals.
• Ability to work in a high-velocity engineering environment and translate complex, ambiguous requirements into concrete, scalable engineering solutions.

Responsibilities

• Design and implement advanced batch scheduling architectures using frameworks like Volcano or YuniKorn to support multi-node gang scheduling.
• Develop and manage cluster-wide admission control and sophisticated job queueing mechanisms utilizing Kueue to manage high-volume AI workload traffic.
• Leverage Kubernetes Dynamic Resource Allocation (DRA) and custom scheduler plugins to manage complex accelerator requests natively.
• Architect topology-aware pod placement strategies that optimize for low-latency communication via NVLink and InfiniBand fabrics.
• Implement automated GPU sharing technologies (e.g., MIG, time-slicing) and multi-tenancy isolation policies to maximize cluster-wide utilization.
• Collaborate with the GPU Systems and Storage teams to ensure the scheduling layer is tightly integrated with bare-metal hardware and storage I/O patterns.
• Drive the reliability and scalability of the scheduling stack, resolving resource contention and deadlock scenarios in large-scale HPC environments.
• Mentor junior engineers and conduct design reviews to maintain architectural excellence in our orchestration layer.

Skills

Kubernetes scheduling

Distributed systems

AI workload patterns

PyTorch Distributed

Ray

MPI

Leadership

Education

Bachelor's or Master's in CS/EE

Tools

Terraform

Go-based Operators

Volcano

YuniKorn

Kueue

Job description

Bitdeer Group is seeking a Staff AI Scheduling & Orchestration Engineer to lead the workload placement logic for our AI-native NeoCloud platform.

You'll tackle advanced batch scheduling, multi-node gang scheduling, and GPU-accelerated workloads, shaping a high-performance fabric across NVLink and InfiniBand. This role blends distributed systems with AI at scale and offers impact across our compute fleets.