Senior Accelerated Computing Architect

Nvidia

Quick summary

Work type: On-site
Location: Santa Clara, CA
Salary: $184,000–$287,500 / yr
Posted: 53 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $203k

This role $236k

$151k most similar roles pay here $302k

This role pays more than 87% of similar roles. Most pay $170,000–$235,750 — the shaded band above. At the midpoint, this role pays about $236k versus about $203k 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 563 open roles on FindRole.

Listed pay typically runs $168,000–$264,500 across 556 roles with salary data.

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View all roles at Nvidia

At a glance

TL;DR · Senior Accelerated Computing Architect

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As a Senior Accelerated Computing Architect at NVIDIA, you will join a dynamic team focused on developing cutting-edge software and system architectures for high-performance computing, scientific computing, machine learning, AI, datacenters, and automotive applications. Your daily responsibilities include conducting in-depth analysis and optimization to enhance performance on current and next-generation GPUs, creating optimized parallel algorithms and reference codes, and collaborating with hardware design, software engineering, product, and research teams to guide the direction of accelerated computing initiatives. You will also engage in co-design efforts by diving into various applications and communicating your findings through white papers, conference presentations, blog posts, and patent applications. To excel in this role, you should have an MS or Ph.D. in Computer Science, Engineering, or a related field, with extensive experience in GPU programming using CUDA or OpenCL, proficiency in C/C++, and familiarity with threading APIs for multicore CPUs and Unix IPC mechanisms.

Skills

CUDA OpenCL MPI NVSHMEM C C++ Python UnixIPC Linux

What you'll do

Perform in-depth analysis and optimization for NVIDIA GPUs.
Create and optimize core parallel algorithms and data structures for GPU solutions.
Analyze hardware-software interplay on algorithms, programming models, and applications.
Guide accelerated computing direction by collaborating with cross-functional teams.
Dive into accelerated computing applications to facilitate software-hardware co-design.

What we're looking for

MS or Ph.D. in Computer Science, Engineering, or equivalent experience.
6+ years of relevant work experience in accelerated computing.
Expertise in GPU programming using CUDA or OpenCL.
Proficiency in C and C++ with knowledge of software design techniques.
Experience with multi-node communication APIs like MPI or NVSHMEM.
Strong problem-solving skills and excellent time management abilities.

Senior SoC Performance Architect

Qualcomm

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C++ Python Perl AMBA CHI AXI protocol LPDDR5 DDR5 PCIe CXL CCIX SoC performance modeling RTL development Pre-silicon testing Post-silicon debugging Performance analysis Power modeling

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