Lead AI Scheduling & Orchestration Engineer

Bitdeer; San Jose (CA); On-site; USD 180,000 - 230,000; Full time

Job summary

Bitdeer is seeking a Staff AI Scheduling & Orchestration Engineer to lead workload placement for our NeoCloud platform. You will tackle GPU stranding, maximize hardware utilization, and build a scheduling fabric aware of NVLink and InfiniBand topology.

You will operate at the intersection of distributed systems and AI, guiding architecture for massive-scale distributed training and inference with high efficiency across our compute fleet.

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 Kubernetes scheduling experience.
• 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 scheduling challenges in 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.
• Ability to work in a high-velocity engineering environment and translate complex requirements into scalable 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.
• Leverage Kubernetes Dynamic Resource Allocation (DRA) and custom scheduler plugins to manage complex accelerator requests.
• 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 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

Distributed systems engineering

Leadership & mentoring

Technical communication

AI workload patterns

GPU scheduling

Go-based Operators

Infrastructure as Code

Education

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

Tools

Volcano

YuniKorn

Kueue

Terraform

Go-based Operators

PyTorch Distributed

Ray

MPI

NVLink

InfiniBand

Job description

Bitdeer is seeking a Staff AI Scheduling & Orchestration Engineer to lead workload placement for our NeoCloud platform. You will tackle GPU stranding, maximize hardware utilization, and build a scheduling fabric aware of NVLink and InfiniBand topology.

You will operate at the intersection of distributed systems and AI, guiding architecture for massive-scale distributed training and inference with high efficiency across our compute fleet.