Senior Accelerated Computing Architect

Nvidia

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Santa Clara, CA
Salary: $184,000–$287,500 / yr
Employment: Full-time
Posted: 5 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $207k

This role $236k

$151k $302k

below market most similar roles pay here above market

This role pays more than 82% of similar roles. Most pay $179,075–$235,750 — the blue band above. At the midpoint, this role pays about $236k versus about $207k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 1792 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1179 roles with salary data.

Most-posted roles

View all roles at Nvidia

At a glance

TL;DR · Senior Accelerated Computing Architect

Role Posting Log in to save

The Senior Accelerated Computing Architect joins the team developing software and system architectures for high performance computing, scientific computing, machine learning, AI, datacenter, and automotive computing. The role involves performing in-depth analysis and optimization to ensure peak performance on current and next-generation GPUs. Key responsibilities include creating and optimizing core parallel algorithms, data structures, and reference codes while analyzing the interplay of hardware and software architectures. The architect will collaborate with hardware design, software engineering, product, and research teams to guide accelerated computing direction and facilitate software-hardware co-design. Required skills include strong mathematical fundamentals in linear algebra and numerical methods, proficiency in C and C++, and hands-on experience with CUDA or OpenCL. Familiarity with MPI, NVSHMEM, and Python is also preferred.

Skills

CUDA C++ C OpenCL MPI NVSHMEM OpenSHMEM Python IPC Linear Algebra Numerical Methods Software Design Algorithms GPU Programming Multi-node Communication

What you'll do

Perform in-depth analysis and optimization to maximize performance on current and next-generation NVIDIA GPUs.
Create and optimize core parallel algorithms, data structures, and reference codes for GPU solutions.
Analyze the interplay between hardware and software architectures on core algorithms and programming models.
Facilitate software-hardware co-design by diving into specific accelerated computing applications.
Guide the direction of accelerated computing through collaboration with hardware, software, product, and research teams.
Author and present technical work through white papers, conference publications, blog posts, and patent applications.

What we're looking for

An MS or Ph.D. in Computer Science, Computer Engineering, or Electrical Engineering, or equivalent experience.
6+ years of relevant work experience.
Strong mathematical fundamentals, including linear algebra and numerical methods.
Hands-on experience with the massively parallel GPU programming model, such as CUDA or OpenCL.
Strong knowledge of C and C++ with a solid understanding of software design, programming techniques, and algorithms.
Familiarity with APIs for multi-node communication, like MPI or OpenSHMEM/NVSHMEM (preferred).
Familiarity with threading APIs for multicore CPUs and Unix-style Inter-process Communication (IPC) APIs (preferred).
Familiarity with Python (preferred).

Save