Cloud Services Software Engineer

at Nvidia

USD 152,000-287,500 per year

SENIOR

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 4 API AWS @ 4 Azure @ 4 Cloud Computing @ 4 Deep Learning @ 4 Distributed Systems @ 6 Docker @ 4 GCP @ 4 GPU Go @ 6 HPC @ 4 JAX @ 4 Kubernetes @ 4 Machine Learning Microservices PyTorch @ 4 Python @ 6 Slurm @ 4 TensorFlow @ 4

Details

Joining NVIDIA's DGX Cloud Team means contributing to the infrastructure that powers AI research. The team focuses on optimizing the efficiency and resiliency of machine learning workloads and developing scalable AI infrastructure tools and services. The objective is to provide AI researchers with a stable, scalable environment and the resources required to support innovation.

As a Senior Software Engineer, you will develop and optimize AI infrastructure services for DGX Cloud, focusing on cloud services software architecture and the full resiliency stack required for high AI performance and reliability.

Responsibilities

Develop solutions at the intersection of machine learning, distributed systems, and high-performance computing.
Design, develop, and optimize microservices orchestrated by Kubernetes to support large-scale AI training workflows on AI training supercomputers hosted by major cloud service providers.
Co-design and implement APIs that integrate services with NVIDIA's resiliency stacks, including tier-0 telemetry, break/fix automation, checkpointing, and execution systems.
Build a submission abstraction that enables model engineers and training platforms or frameworks to submit long-running training jobs while hiding infrastructure failure complexity.
Implement job lifecycle management with automatic restarts after failures, efficient resource usage, and timely user notifications.
Develop modular services that can be coordinated with and deployed on on-premises AI clusters using NVIDIA hardware and cloud services.

Requirements

Bachelor's degree or higher in Computer Science or a related technical field, or equivalent experience.
At least 5 years of hands-on backend development experience, preferably with Python, Go, C++, or similar high-performance languages.
A consistent track record of building and scaling large-scale distributed systems.
Experience with cloud computing platforms such as AWS, Azure, and GCP.
Experience with container technologies including Docker and Kubernetes.
Experience with HPC or AI platforms such as Slurm.

Preferred Qualifications

Real-world experience with deep learning frameworks and orchestrators such as PyTorch, TensorFlow, JAX, and Ray.
Experience developing framework plugin architectures that integrate frameworks with cluster schedulers in a user-visible manner.
Strong understanding of NVIDIA GPUs, network technologies, and failure patterns.
Experience with AI models and AI-based tools.
Code contribution references.

Compensation and Benefits

The base salary range is USD 152,000–241,500 for Level 3 and USD 184,000–287,500 for Level 4. Salary is determined based on location, experience, and the pay of employees in similar positions. The role is also eligible for equity and benefits.

Applications will be accepted at least until October 25, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.