Senior Systems Software Engineer - NV Cloud Functions

NVIDIA•Santa Clara, CA

12d•$152,000 - $287,500

About The Position

NVIDIA’s Cloud Functions team is seeking a motivated, product-minded AI/ML engineer with expertise in AI platform engineering at scale. The team builds and operates a serverless deployment platform for AI applications, scaling inference workloads through globally distributed orchestration across GPU-backed, cloud-agnostic Kubernetes clusters. The engineer will help define cloud engineering paradigms for AI at scale and work with internal and external users to improve the NVCF platform.

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 in deep learning and machine learning, including expertise with AI/DL frameworks and inference software such as SGLang, vLLM, TensorRT-LLM, or Dynamo.
Knowledge of CPU and GPU architecture.
Excellent interpersonal skills, including the ability to explain sophisticated technical topics to non-experts.
Experience designing, implementing, and releasing AI/ML products to market, and familiarity with all aspects of the software development lifecycle.

Nice To Haves

A demonstrated desire and ability to share knowledge with clients, partners, and coworkers.
Expertise demonstrated through projects or open-source contributions in HPC, data analytics, machine learning, deep learning, cloud-native projects, Kubernetes, Slurm, or enabling GPU workloads.
Demonstrated willingness and ability to explore unfamiliar areas and tackle complex problems.
Prior experience building distributed systems.

Responsibilities

Understand user challenges and constraints, translate them into product requirements and solutions, and accelerate delivery of AI models and inference hosted on the NVCF platform.
Lead implementation of key features and conduct user-acceptance testing, load testing, and performance evaluations, with an emphasis on customer experience, optimization, and platform reliability.
Mentor and embed with engineering teams building products on the platform, advising on best practices for scalable, high-performance AI/ML workloads and ML reliability engineering.
Produce reference architectures for customer use cases using NVCF features and current AI technologies.
Guide customer issues through to resolution and provide timely warnings about issues and risks.
Evaluate emerging technologies and tools to inform a competitive product and forward-looking roadmap.