Principal Software Architect, AI and HPC
We are now looking for a Principal Software Architect for AI and HPC.
At NVIDIA, we are advancing the frontiers of AI capabilities. We seek an expert in high-performance computing and AI to design and develop software resiliency features for training AI models on the world’s most powerful and largest supercomputers.
In this role, you will outline mission requirements for ultra large-scale AI supercomputers, thoroughly investigate and evaluate RAS feature designs, establish software requirements and evaluation metrics, and oversee the complete implementation of RAS features in software. As a leader in HPC and AI software development, you will interact with multiple teams across the organization. Your responsibilities include conducting regular reviews and check-ins with execution teams, ensuring the timely delivery of essential RAS software features such as checkpoint-recovery logic, error detection and attribution, error containment, SDC detection, and other related RAS elements. Leading cross-organizational efforts among various stakeholders and teams, you will coordinate priorities with senior leadership, provide timely updates, and ensure adequate resourcing for the projects.
What You'll Be Doing:
Collaborate with both internal and external customers and partners to define innovative Reliability, Availability, and Serviceability (RAS) requirements and objectives for present and future AI supercomputing products.
Oversee and guide the development of RAS features across the entire AI stack, encompassing aspects from job-level scheduling and AI application frameworks (such as PyTorch), down to driver-level and hardware health monitoring on GPUs.
Develop and maintain comprehensive software roadmaps, ensuring alignment with diverse engineering teams and synchronizing with engineering and product leadership for strategic coherence.
Drive successful implementation and execution of RAS features in software, with demonstrable improvements in end-to-end metrics such as availability during large-scale training runs.
What We Need to See:
A Master's or Ph.D. in Computer Science, Electrical or Computer Engineering from a reputed university, or equivalent professional experience.
15+ years of industry experience in systems architecture or related fields, demonstrating a deep understanding of system complexities.
Proven ability to work and communicate effectively in a collaborative environment, bridging multiple engineering disciplines.
At least 5 years of hands-on experience in software development, preferably in high-complexity projects involving HPC or AI.
Ways to Stand Out From the Crowd:
Demonstrated experience with large-scale AI supercomputing applications, particularly in training and inference stages.
In-depth knowledge of the requirements for large-scale AI workload training and inference.
A strong passion for and experience in developing system architectures tailored for AI applications, encompassing CPU, GPU, memory, storage, and networking.
Hands-on involvement in the entire lifecycle – from design to deployment – of large-scale High-Performance Computing (HPC) systems.
Practical experience in adopting and implementing HPC software development practices in large-scale system environments.
As NVIDIA makes inroads into the Datacenter business, our team plays a central role in getting the most out of our exponentially growing datacenter deployments as well as establishing a data-driven approach to hardware design and system software development. We collaborate with a broad cross section of teams at Nvidia ranging from DL research teams to CUDA Kernel and DL Framework development teams, to Silicon Architecture Teams. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative and autonomous, we want to hear from you!The base salary range is 268,000 USD - 414,000 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.