Principal AI and ML Infra Software Engineer, GPU Clusters
At a glance
Senior ML Platform & Ops role at NVIDIA. US, CA, Santa Clara · full-time · $272,000–$431,250 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Work with AI and ML researchers to uncover infrastructure gaps, then turn their needs into practical improvements
- Find what slows researchers down and lead efforts to remove those bottlenecks, setting longer-term plans for the work
- Track infrastructure performance and tune it for availability, scale and efficient use of computing resources
- Define measures of researcher efficiency and coordinate with data engineering and DevOps teams on shared infrastructure
- Assess new AI and ML methods and frameworks, then make the case for adopting useful ones
What you bring
- A computer science degree or comparable background, or equivalent practical experience
- At least fifteen years working with AI/ML and high-performance computing systems
- Practical experience operating HPC infrastructure and strong knowledge of GPUs, storage, scheduling, networking and containers
- Experience improving large distributed training with PyTorch, NeMo or JAX, plus knowledge of data, training and inference workflows
- Programming experience with Python, Go or Bash, alongside cloud platforms and parallel computing approaches
Who this fits
This is a principal-level engineering role for someone who can lead infrastructure improvements while working directly with research teams. It suits an engineer comfortable coordinating across technical groups and shaping long-term plans for GPU cluster infrastructure.
From the employer
We are seeking a Principal AI and ML Infra Software Engineer, GPU Clusters at NVIDIA to join our Hardware Infrastructure team. As an Engineer, you will have a pivotal role in enhancing efficiency for our researchers by implementing progressions throughout the entire stack. Your main task will revolve around collaborating closely with customers to pinpoint and address infrastructure deficiencies, facilitating groundbreaking AI and ML research on GPU Clusters. Together, we can craft potent, effective, and scalable solutions as we mold the future of AI/ML technology!
What you will be doing:
Engage closely with our AI and ML research teams to discern their infrastructure requirements and barriers, converting those insights into actionable improvements.
Proactively identify researcher efficiency bottlenecks and lead initiatives to systematically improve it. Drive the direction and long-term roadmaps for such initiatives.
Monitor and optimize the performance of our infrastructure ensuring high availability, scalability, and efficient resource utilization.
Help define and improve important measures of AI researcher efficiency, ensuring that our actions are in line with measurable results.
Work closely with a variety of teams, such as researchers, data engineers, and DevOps professionals, to develop a cohesive AI/ML infrastructure ecosystem.
Keep up to date with the most recent developments in AI/ML technologies, frameworks, and successful strategies, and advocate for their integration within the organization.
What we need to see:
BS or similar background in Computer Science or related area (or equivalent experience).
15+ years of demonstrated expertise in AI/ML and HPC tasks and systems.
Hands-on experience in using or operating High Performance Computing (HPC) grade infrastructure as well as in-depth knowledge of accelerated computing (e.g., GPU, custom silicon), storage (e.g., Lustre, GPFS, BeeGFS), scheduling & orchestration (e.g., Slurm, Kubernetes, LSF), high-speed networking (e.g., Infiniband, RoCE, Amazon EFA), and containers technologies (Docker, Enroot).
Capability in supervising and improving substantial distributed training operations using PyTorch (DDP, FSDP), NeMo, or JAX. Moreover, an in-depth understanding of AI/ML workflows, involving data processing, model training, and inference pipelines.
Proficiency in programming & scripting languages such as Python, Go, Bash, as well as familiarity with cloud computing platforms (e.g., AWS, GCP, Azure) in addition to experience with parallel computing frameworks and paradigms.
Dedication to ongoing learning and staying updated on new technologies and innovative methods in the AI/ML infrastructure sector.
Excellent communication and collaboration skills, with the ability to work effectively with teams and individuals of different backgrounds.
NVIDIA offers competitive salaries and a comprehensive benefits package. Our engineering teams are growing rapidly due to outstanding expansion. If you're a passionate and independent engineer with a love for technology, we want to hear from you.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD.You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until October 18, 2026.This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.