Staff AI Scheduling & Orchestration Engineer at Bitdeer Technologies Group
Austin, TX
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Aug 19, 2026
Austin, TX
Sep 25, 2026
What this job asks for AI summary
This Staff-level role owns the workload scheduling and orchestration layer of an AI-native cloud platform, with a focus on eliminating GPU stranding and maximizing utilization across large GPU fleets. The engineer will design and build advanced batch scheduling systems, topology-aware pod placement, GPU sharing mechanisms, and admission control pipelines on top of Kubernetes. It suits a distributed-systems specialist with deep Kubernetes internals knowledge and hands-on experience running HPC or large-scale AI training environments.
Staff level · 6+ years · Bachelor's required · Full-time
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“or” means any one of them counts — you don't need all of them.
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How this req sits in the market our data
Rare in this occupation — lead with these, and say what you built with them.
What the occupation pays Median $138,970 (middle half $107,524–$175,762).
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Aug 20, 2026. It is a model, not a headcount.
Why we read it this way (8)
The posting is headquartered in Singapore and lists data centers across multiple countries; no specific city or US-based work location is stated, so this role is treated as non-US and no CBSA is assigned.
The degree requirement lists 'Bachelor's or Master's' — Bachelor's is captured as the minimum hard gate.
Volcano and YuniKorn appear together as interchangeable batch scheduling framework options ('like Volcano or YuniKorn'); they are combined into one skill with YuniKorn as an alternative.
PyTorch Distributed, Ray, and MPI are listed as interchangeable distributed training framework examples ('e.g., PyTorch Distributed, Ray, MPI'); Ray and MPI are captured as alternatives.
Terraform and Go-based Operators are listed together as infrastructure-as-code examples; Terraform is named as the primary skill and Go is extracted separately as it is a distinct language used for writing Kubernetes Operators.
GPU MIG and time-slicing are listed together as GPU sharing technologies; MIG is the named product and is captured as the primary skill.
The alt SOC (15-1244) is noted because the role has a significant infrastructure operations dimension, but the primary work — writing custom scheduler plugins, operators, and orchestration code — firmly points to Software Developers (15-1252).
Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): Kubernetes Dynamic Resource Allocation.
Read the full posting
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