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Senior Software Engineer, High-Performance Computing (HPC) Scheduling & Distributed Systems
Relocation
AI Summary
Design, develop, and maintain large-scale scheduling software for HPC, AI, and production workloads. Lead backend services, distributed systems, and automation in Go, Kubernetes, and cloud environments. Collaborate on open-source projects like Armada while ensuring reliability, scalability, and performance in production infrastructure.
Key Highlights
Lead development of distributed scheduling systems for HPC/AI workloads in production environments
Primary focus on Go-based backend services, Kubernetes, and cloud-native infrastructure
Ownership of open-source project Armada and internal platform tooling with emphasis on reliability and scalability
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Key Responsibilities
Design, build, and maintain scalable backend services, APIs, and distributed systems for HPC/AI workloads
Develop and optimize scheduling software (including contributions to open-source project Armada) in Go
Ensure platform reliability, performance, and maintainability through automation, observability, and testing
Troubleshoot and resolve complex distributed systems issues across cloud, Linux, and Kubernetes environments
Collaborate on CI/CD pipelines, monitoring (Prometheus/Grafana), and data interactions (PostgreSQL)
Technical Skills Required
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Benefits & Perks
100% company-paid benefits
Competitive base salary ($170,000–$250,000) + performance bonus
Relocation assistance available for non-local candidates
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Nice to Have
Experience with HPC/AI infrastructure or batch scheduling
Contributions to open-source projects
Familiarity with non-relational databases or high-throughput systems
Job Description
Senior Software Engineer, HPC Scheduling
Location: Dallas, TX | Hybrid
Type: Direct Hire
Relocation: Available for non-local candidates
Compensation
Base salary: $170,000 – $250,000 + performance bonus
Benefits: 100% company-paid benefits
Overview
GTN is seeking a Senior Software Engineer, HPC Scheduling to help design, build, and maintain large-scale scheduling software that supports demanding HPC, AI, research, and production workloads.
This role sits on a highly technical scheduling team responsible for developing distributed systems, backend services, APIs, tooling, and automation that keep a high-scale compute platform reliable, performant, and maintainable.
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