3 days ago
Base Salary
$272k - $431k/yr
Responsibilities
- Partner with AI and ML research teams to understand infrastructure requirements and convert them into actionable improvements.
- Identify researcher efficiency bottlenecks and lead systematic improvement initiatives and long-term roadmaps.
- Monitor and optimize infrastructure performance, availability, scalability, and resource utilization.
- Define and improve measurable metrics for AI researcher efficiency.
- Collaborate with researchers, data engineers, and DevOps professionals to develop an AI/ML infrastructure ecosystem.
- Track developments in AI/ML technologies and advocate for their organizational adoption.
Requirements
- A BS or similar background in Computer Science or a related area, or equivalent experience.
- 15+ years of demonstrated experience with AI/ML and HPC tasks and systems.
- Hands-on experience operating HPC-grade infrastructure and knowledge of GPUs or custom silicon, storage, scheduling and orchestration, high-speed networking, and containers.
- Experience supervising and improving distributed training operations using PyTorch, NeMo, or JAX, with understanding of data processing, model training, and inference pipelines.
- Proficiency in Python, Go, and Bash, familiarity with AWS, GCP, or Azure, and experience with parallel computing frameworks and paradigms.
- Commitment to ongoing learning in AI/ML infrastructure technologies and methods.
- Strong communication and collaboration skills across teams and backgrounds.
Benefits
- Competitive base salary and comprehensive benefits package.
- Eligibility for equity and benefits.
- Existing vacancy with applications accepted at least until October 18, 2026.
Categories
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.