Senior Math Libraries Engineer, Direct Sparse Solvers

Nvidia

Confirmed live today Trusted
Remote

Quick summary

Work type
Remote
Location
Santa Clara, CA
Salary
$184,000–$287,500 / yr
Employment
Full-time
Posted
140 days ago
Freshness
Confirmed live today

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Competitive pay

How this pay compares to similar roles

Similar $219k
This role $236k
$162k $301k
below market most similar roles pay here above market

This role pays more than 65% of similar roles. Most pay $196,750–$241,750 — the blue band above. At the midpoint, this role pays about $236k versus about $219k 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 1623 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1110 roles with salary data.

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At a glance

TL;DR · Senior Math Libraries Engineer, Direct Sparse Solvers

The Senior Math Libraries Engineer joins the development team for cuDSS, a CUDA library for direct solvers for sparse linear systems. In this role, you will design, implement, and optimize direct sparse solvers for existing and future GPU architectures. You will collaborate with library engineers, QA engineers, and interns to manage all development aspects from design to release. Key responsibilities include re-architecting libraries to improve quality and performance while contributing to technical roadmaps. You must possess expertise in C++, CUDA, MPI, OpenMP, OpenACC, and pthreads. Required skills include numerical analysis, floating-point arithmetic, and sparse linear algebra primitives like matrix-vector products. The work addresses technical challenges in scientific and engineering simulations, including computer aided engineering, electronic design automation, optimization, and quantum chemistry.

What you'll do

  • Design, implement, and optimize direct sparse solvers for current and future GPU architectures.
  • Craft high-performance algorithms and kernels for direct sparse solvers.
  • Manage all library development aspects from initial design and implementation to testing and release.
  • Define technical roadmaps by identifying feature and performance requirements with product management.
  • Improve library quality, performance, and maintainability through re-architecting and innovative software practices.
  • Debug and optimize high-performance numerical software using C++ and parallel programming technologies.
  • Implement sparse linear algebra primitives such as matrix-vector products and triangular solves.

What we're looking for

  • PhD or MSc degree in Computer Science, Computational Science and Engineering, Applied Mathematics, or a related field (or equivalent experience).
  • 5+ years of experience developing, debugging, and optimizing high-performance numerical software using C++ and parallel programming.
  • Experience using CUDA, MPI, OpenMP, OpenACC, pthreads, or equivalent technologies (preferred).
  • Strong fundamentals in floating-point arithmetic, numerical analysis, and implementation of sparse linear algebra primitives.
  • Experience in developing, maintaining, and testing scientific computing libraries.
  • Strong collaboration, communication, and documentation habits.
  • Familiarity with direct solver techniques such as reordering, multi-frontal factorizations, and numerical pivoting strategies (preferred).
  • Good knowledge of CPU and/or GPU hardware architecture and low-level GPU performance optimization (preferred).

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