GPU Fleet Engineer: Build Observability & Automation

Iceberg; New York (NY); On-site; USD 120,000 - 170,000; Full time

Job summary

Iceberg is seeking a Software Engineer to join its high-performance GPU infra team in New York. You will build tooling for fleet management, monitoring and network configuration, and work across the stack from applications to kernel drivers to diagnose and resolve issues.

You will own GPU fleet automation, workload tuning, and data-driven optimization to improve utilization, with a focus on observability and scalable infrastructure in a rapidly growing environment.

Qualifications

• 2+ years of relevant software engineering experience, including strong Python development.
• Hands-on experience managing and troubleshooting GPU infrastructure.
• Strong CS fundamentals and sound software design instincts.
• Solid Linux/UNIX experience and comfort with open-source software.
• Strong debugging skills and a methodical approach to problem solving.
• Experience with configuration management and monitoring technologies.
• BS/MS in Computer Science or a related field.

Responsibilities

• Build and maintain tooling for GPU fleet management, monitoring, metrics, maintenance and network configuration.
• Troubleshoot issues across applications, networking, Linux, drivers and the kernel.
• Work with engineering teams to tune workloads and improve GPU utilization.
• Analyse GPU job data to identify trends, inefficiencies and opportunities for improvement.
• Automate manual, slow or error-prone processes.

Skills

Python development

GPU infrastructure troubleshooting

CS fundamentals

Linux/UNIX experience

Debugging skills

Configuration management & monitoring

Software engineering

Education

BS/MS in Computer Science or related field

Job description

Iceberg is seeking a Software Engineer to join its high-performance GPU infra team in New York. You will build tooling for fleet management, monitoring and network configuration, and work across the stack from applications to kernel drivers to diagnose and resolve issues.

You will own GPU fleet automation, workload tuning, and data-driven optimization to improve utilization, with a focus on observability and scalable infrastructure in a rapidly growing environment.