10 days ago
Base Salary
$184k - $357k/yr
Responsibilities
- Build and deploy custom AI solutions on NeoCloud platforms and NVIDIA Cloud Partners, including distributed training, inference optimization, and MLOps pipelines.
- Act as the primary technical contact for internal and external customers and partners and guide joint engagements on DGX Cloud.
- Diagnose and solve complex full-stack AI and ML problems in production.
- Profile and tune large-scale training and inference workloads to reduce latency, cost, and operational risk.
- Develop open-source tools and reference architectures for machine learning and AI workloads, pipelines, and systems at scale.
- Support LLM performance evaluation and new hardware in open-source frameworks.
Requirements
- A BS, MS, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field, or equivalent experience.
- 8+ years of experience in technical roles such as data science, data engineering, or ML engineering, ideally on large-scale production systems.
- AI/ML experience across multiple phases of the machine learning lifecycle, from exploratory analysis through production systems.
- Experience with Linux, batch schedulers, Kubernetes, distributed filesystems, and advanced datacenter-scale networking.
- Scripting and programming skills with bash and Python, plus systems programming experience with C++, Go, or Rust.
- Experience using machine learning or deep learning frameworks for training and inference.
- Excellent communication and technical presentation skills for engineering and leadership audiences.
- A record of engineering discipline and execution on individual or collaborative projects.
- Preferred qualifications include open-source community experience; NVIDIA ecosystem experience with DGX systems, CUDA, NeMo, RAPIDS, Triton, NIM, InfiniBand, NVLink, and RoCE; security-critical ML systems experience; distributed training and inference experience; and familiarity with cloud-native MLOps practices and cross-layer systems debugging.
Benefits
- Competitive base salary and generous benefits package.
- Eligible for equity and benefits.
- Applications will be accepted at least until November 3, 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.