1 day ago
Base Salary
$152k - $288k/yr
Responsibilities
- Translate user challenges into product requirements and solutions for AI model and inference delivery on the NVCF platform.
- Lead implementation of key platform features and conduct user-acceptance testing, load testing, and performance evaluations.
- Advise engineering teams on best practices for AI/ML workloads at scale, including ML reliability engineering.
- Produce reference architectures for customer use cases using current NVCF features and AI technologies.
- Shepherd customer issues to resolution and communicate issues and risks in a timely manner.
- Evaluate emerging technologies and tooling to support the product roadmap.
Requirements
- Master's, PhD, or equivalent experience in Computer Science, Artificial Intelligence, Applied Math, or a related field.
- At least 2 years of work experience with Python, Rust, Golang, Linux, or Bash.
- Experience with deep learning and machine learning, including AI/DL frameworks and inference software such as SGLang, vLLM, TensorRT-LLM, or Dynamo.
- Knowledge of CPU and GPU architecture.
- Experience designing, implementing, and releasing AI/ML products to market across the software development lifecycle.
- Strong interpersonal and technical communication skills, including explaining sophisticated topics to non-experts.
- Preferred experience or contributions in HPC, data analytics, machine learning, deep learning, cloud-native projects, Kubernetes, Slurm, GPU workloads, or distributed systems.
Benefits
- Competitive base salary and comprehensive benefits package.
- Eligibility for equity and benefits.
- Applications will be accepted at least until September 13, 2026.
- This posting is for an existing vacancy.
Tech Stack
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.