Staff Software Engineer (AI Runtime)

TL;DR

Staff Software Engineer (AI Runtime): Building and scaling the managed GPU training platform for large-scale AI models with an accent on distributed training performance and fault tolerance. Focus on designing multi-node orchestration, optimizing GPU efficiency, and developing resilience foundations for frontier-scale foundation models.

Location: Mountain View, California or San Francisco, California

Salary: $190,000 — $265,000 USD

Company

hirify.global is a data and AI company providing a Data Intelligence Platform that unifies data, analytics, and AI for over 10,000 organizations worldwide.

What you will do

• Drive the architecture and evolution of the AI Runtime (AIR) managed GPU training platform for scalable, high-throughput training.
• Solve complex problems in multi-node orchestration, distributed parallelism strategies, and GPU scheduling.
• Optimize GPU efficiency and training performance to raise utilization and lower cost per training run.
• Build resilience and observability foundations to detect and recover from hardware and software failures.
• Partner with product and research teams to shape APIs, CLI, and the developer experience for production training jobs.
• Mentor senior engineers and champion engineering excellence to shape the long-term technical direction of AI training infrastructure.

Requirements

• 10+ years of experience building and operating large-scale distributed systems, GPU training infrastructure, or ML systems.
• Hands-on experience with distributed training frameworks such as PyTorch, FSDP, DeepSpeed, or Megatron.
• Deep understanding of parallelism strategies (data, tensor, pipeline, and sequence parallelism).
• Strong grasp of GPU performance fundamentals, including NVLink, InfiniBand, and collective communication.
• Experience building managed, multi-tenant cloud platform products with clear SLAs and SLOs.
• BS in Computer Science or a related field (MS or PhD preferred).

Culture & Benefits

• Comprehensive benefits and perks tailored to the employee's region.
• Opportunity to work on the most demanding workloads in computing, including frontier-scale foundation models.
• Collaborative environment partnering across product, research, and platform teams.
• Commitment to diversity, inclusion, and equal employment opportunity standards.