Senior Engineer, Math Libraries, Consumer and Embedded Platforms

Nvidia

Confirmed live yesterday High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Santa Clara, CATXNYWACAMA
Salary
$152,000–$241,500 / yr
Employment
Full-time
Posted
7 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $191k
This role $197k
$141k $252k
below market most similar roles pay here above market

This role pays more than 54% of similar roles. Most pay $151,356–$231,150 — the blue band above. At the midpoint, this role pays about $197k versus about $191k for comparable roles.

Based on 240 similar postings.

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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 1472 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1109 roles with salary data.

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At a glance

TL;DR · Senior Engineer, Math Libraries, Consumer and Embedded Platforms

JOB TITLE: Senior Engineer, Math Libraries - Consumer and Embedded Platforms The Senior Engineer, Math Libraries - Consumer and Embedded Platforms joins the team enabling CUDA Math Libraries on new and specialized platforms. This role involves ensuring platform readiness for libraries including cuBLAS, cuSPARSE, cuSOLVER, and cuFFT through integration, functional qualification, compliance, and performance readiness. Daily responsibilities include performing defect triage, identifying performance targets, and establishing platform-specific qualification and validation pipelines. The position requires expertise in high-performance numerical software, GPU kernel development, and parallel programming using C++ and Python. Candidates must understand fundamental numerical methods for science, engineering, and deep learning. Key technical skills include experience with object-oriented programming, CI/CD systems, JIRA, and parallel programming models like MPI, OpenMP, OpenACC, and pthreads to solve complex computational problems in AI and scientific simulations.

What you'll do

  • Enable CUDA Math Libraries on new and specialized platforms for integration and functional qualification.
  • Perform defect triage to isolate and fix platform-specific and library-specific software bugs.
  • Identify performance targets for new platforms and establish performance testing protocols.
  • Fix performance regressions to ensure high-quality execution on all target platforms.
  • Collaborate with infrastructure teams to build platform-specific qualification and validation pipelines.
  • Ensure functional correctness and compliance for libraries including cuBLAS, cuSPARSE, and cuFFT.

What we're looking for

  • PhD or MSc degree in Computational Science and Engineering, Computer Science, Applied Mathematics, or a related field (or equivalent experience).
  • 5+ years of experience developing high-performance numerical software.
  • Experience with C++ and Python for object-oriented programming, large system software architecture, and performance optimization of HPC software.
  • Experience with parallel computing, testing, maintenance, and software development practices like CI/CD systems and JIRA.
  • Strong understanding of fundamental numerical methods and computations in science, engineering, and/or deep learning.
  • Experience with CUDA, GPU-accelerated computing, and parallel programming (e.g. MPI, OpenMP, OpenACC, pthreads) (preferred).
  • Familiarity with math libraries such as BLAS, LAPACK, FFT, and sparse solvers (preferred).
  • Experience with cross-platform software development, platform bring-up, or safety-critical/embedded environments (preferred).

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