2 days ago
Base Salary
$152k - $288k/yr
Responsibilities
- Lead implementation of key AI/ML platform features and conduct user-acceptance testing, load testing, and performance evaluations.
- Serve as a subject matter expert translating user challenges into product requirements and solutions for AI model deployment and inference.
- Mentor engineering teams on best practices for AI/ML workloads, performance, and ML reliability at scale.
- Create reference architectures for customer use cases using NVCF features and current AI technologies.
- Shepherd customer issues to resolution and communicate product risks and issues promptly.
- Evaluate emerging technologies and tooling to support the product roadmap.
Requirements
- Master’s degree, 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, machine learning, 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 communication skills, including the ability to explain sophisticated technical 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 ranging from $152,000 to $241,500 for Level 3 and $184,000 to $287,500 for Level 4.
- Eligibility for equity and benefits.
- Applications accepted at least until November 3, 2026.
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.