Full-Time

Software Engineering Manager

Linear Algebra Libraries

Confirmed live in the last 24 hours

NVIDIA

NVIDIA

10,001+ employees

Designs GPUs and AI computing solutions

Automotive & Transportation
Enterprise Software
AI & Machine Learning
Gaming

Compensation Overview

$224k - $425.5kAnnually

+ Equity

Senior, Expert

Remote in USA + 1 more

More locations: Santa Clara, CA, USA

Category
Engineering Management
Software Development Management
Software Engineering
Required Skills
Python
CUDA
JIRA
C/C++
Requirements
  • PhD or MSc degree in Computational Science and Engineering, Computer Science, Applied Mathematics, or related science or engineering field (or equivalent experience)
  • 8+ overall years of overall experience in developing high-performance numerical software
  • 3+ years of experience recruiting, training and leading software engineering teams
  • Strong fundamentals in numerical methods such as computational linear algebra, linear system solvers, and methods for eigenvalue, singular value, and other decompositions
  • Hands-on experience with user facing API design, object-oriented programming, large system software architecture development, testing, maintenance, and performance optimization of HPC software using C++ and Python
  • Experience with parallel programming, ideally using CUDA, MPI, OpenMP, OpenACC, pthreads
  • Strong collaboration, communication, and documentation habits
  • Background with, and motivation to adopt and advance, software development practices such as CI/CD systems and project management tools such as JIRA
Responsibilities
  • Lead, mentor, and grow your library engineering team
  • Be responsible for the quality and performance of your libraries and the planning and execution of projects
  • Work closely with NVIDIA Research, Developer Technology, and Product Management teams in the areas of scientific computing, programming systems, and AI to help collect requirements for your products as well as contribute to the development of technology roadmaps
  • Interact with external partners and researchers to understand their use cases and requirements
Desired Qualifications
  • Experience developing or using dense linear algebra libraries such as BLAS, LAPACK and their parallel counterparts like PBLAS and SCALAPACK
  • Experience with working in a globally distributed organization
  • Good knowledge of CPU and/or GPU hardware architecture
  • Good understanding of Machine Learning and Deep Learning technologies and experience using one or more deep learning frameworks (e.g., PyTorch, JAX, TensorFlow...)
  • Experience with leading and mentoring teams in dynamic environments such as concurrent HW and SW development

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their main products are GPUs that enhance gaming experiences and support professional applications, along with AI and high-performance computing platforms tailored for developers and data scientists. NVIDIA differentiates itself from competitors by focusing on advanced technology and continuous innovation, ensuring their products meet the evolving needs of users. The company's goal is to lead in AI and HPC solutions, providing powerful tools and services that enable clients to achieve immersive experiences and drive advancements in their respective fields.

Company Stage

IPO

Total Funding

$19.5M

Headquarters

Santa Clara, California

Founded

1993

Growth & Insights
Headcount

6 month growth

0%

1 year growth

0%

2 year growth

0%
Simplify Jobs

Simplify's Take

What believers are saying

  • Acquisition of VinBrain enhances NVIDIA's AI-driven healthcare solutions.
  • Investment in Nebius Group boosts NVIDIA's AI infrastructure capabilities.
  • Partnership with Serve Robotics aligns with NVIDIA's focus on robotics and AI applications.

What critics are saying

  • Increased competition from AI startups like xAI challenges NVIDIA's market position.
  • Serve Robotics' rapid expansion may lead to financial strain if market growth lags.
  • Integration challenges from VinBrain acquisition may affect NVIDIA's operational efficiency.

What makes NVIDIA unique

  • NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.
  • The Omniverse platform enhances NVIDIA's capabilities in industrial AI and digital twins.
  • NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

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Benefits

Company Equity

401(k) Company Match