Senior System Software Engineer - AI Data Platform - Inference Factory Optimization at NVIDIA

Department: Engineer, Sys SW

Language

Setup: Remote
Location: Hanoi · Vnukovo, Moscow
Level: senior
Posted: Jul 13, 2026

Description

NVIDIA is hiring a Senior Software Engineer to design, build, and optimize highly scalable and reliable automation systems for software validation, tuning, and deployment across cloud, on-premises, and specialized hardware environments. The role focuses on infrastructure and tools, performance optimization, system-level programming, distributed systems, CI/CD, and technical strategy, with a requirement of at least five years of relevant software development experience.

Required Skills

C++
Python
Go
Distributed systems
CI/CD
Docker
Kubernetes
Performance optimization

Additional Information

Minimum Education: Bachelor's degree or equivalent experience in Computer Science, Computer Engineering, or a related technical field; a Master's degree or equivalent experience is also acceptable.
Required Previous Experiences: 5+ years of industry experience in software development focused on infrastructure, distributed systems, automation, and/or performance engineering.
Experience with operating system internals, device drivers, memory management, and debugging performance issues in complex compute applications.
Experience designing, building, and operating large-scale distributed systems with knowledge of networking protocols, cluster management, and high-performance interconnects.
Experience building and maintaining automated testing, benchmarking, and continuous integration/continuous deployment pipelines.
Preferred Qualifications: Experience optimizing performance for AI/Machine Learning workloads, especially inference applications, on diverse hardware platforms.
Prior experience building or contributing to large-scale compute infrastructure solutions in cloud environments or on-premises data centers.
Experience with containerization and orchestration technologies, such as Docker and Kubernetes.
Familiarity with performance profiling tools and methodologies for hardware and software systems.
Track record of driving significant efficiency gains or architectural improvements in large-scale systems.