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Internship Linear Algebra Jobs (NOW HIRING)

Nvidia

$104K - $143K/yr

Scoping, designing, and implementing high quality and performance numerical dense linear algebra ... interns. * Working closely with product management and other internal and external customers to ...

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Internship Linear Algebra information

What is the difference between Internship Linear Algebra vs Data Analyst?

AspectInternship Linear AlgebraData Analyst
Required CredentialsBasic knowledge of linear algebra, often student or entry-levelDegree in statistics, mathematics, or related field; some certifications
Work EnvironmentAcademic, research labs, or tech companies; project-basedBusiness settings, corporate offices, or consulting firms
Industry UsageResearch, academia, machine learning, data scienceBusiness intelligence, marketing, finance, operations
Search & Comparison IntentUnderstanding entry-level roles involving linear algebra conceptsComparing roles in data analysis and related fields

Internship Linear Algebra typically involves foundational work in linear algebra concepts within academic or research environments, often as a stepping stone for further studies or careers in data science. Data Analysts focus on interpreting data to inform business decisions, requiring additional skills in statistics and data visualization. While both roles involve data and mathematical skills, their work environments and career paths differ significantly.

What is an Internship in Linear Algebra?

An Internship in Linear Algebra is a temporary position, typically for students or recent graduates, that provides hands-on experience applying linear algebra concepts in real-world settings. Interns may work on projects involving data analysis, machine learning, scientific computing, or engineering tasks that require knowledge of vectors, matrices, and linear transformations. These internships help individuals gain practical skills, build their resume, and explore career opportunities in fields that value mathematical and analytical abilities.

What are the key skills and qualifications needed to thrive as an Internship Linear Algebra, and why are they important?

To thrive in a Linear Algebra internship, you need a solid grasp of linear algebra concepts, mathematical problem-solving abilities, and often enrollment in or completion of a relevant degree program. Familiarity with technical tools such as MATLAB, Python (with libraries like NumPy), or Mathematica, as well as experience with data analysis software, is often expected. Strong analytical thinking, attention to detail, and effective communication help interns interpret results and collaborate with team members. These skills are essential for applying mathematical concepts to real-world problems and contributing meaningfully to research or projects.

What kinds of projects or tasks are typically assigned to interns specializing in Linear Algebra?

Interns focusing on Linear Algebra often work on tasks that involve applying mathematical concepts to real-world problems, such as data analysis, algorithm development, or simulation modeling. You may be asked to assist with optimizing machine learning models, performing matrix computations, or supporting research teams by developing code for numerical experiments. Collaboration with data scientists, engineers, and senior mathematicians is common, providing opportunities to learn from experienced professionals. These experiences give interns valuable exposure to both theoretical and applied aspects of linear algebra in a professional setting.
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What are the most commonly searched types of Linear Algebra jobs? The most popular types of Linear Algebra jobs are:
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Internship Linear Algebra jobs near you
Infographic showing various Internship Linear Algebra job openings in the United States as of July 2026, with employment types broken down into 56% Full Time, and 44% Part Time. Highlights an 65% Physical, and 35% Remote job distribution.
Senior Math Libraries Engineer - Sparse Linear Algebra

Senior Math Libraries Engineer - Sparse Linear Algebra

NVIDIA

Santa Clara, CA • On-site

$55K - $72K/yr

Full-time

Re-posted 20 hours ago

Nvidia rating

9.3

Company rating: 9.3 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

15th of 209 rated software companies

Job description

Job Summary:
NVIDIA is a leading technology company known for its innovations in AI and high-performance computing. They are seeking a Senior Math Libraries Engineer to design, develop, and optimize numerical sparse linear algebra software for GPU architectures, collaborating with various teams to enhance library quality and performance.
Responsibilities:
• Designing, implementing and optimizing scalable high-performance numerical sparse linear algebra software for existing and future GPU architectures
• Working with library engineers, QA engineers, and interns on topics ranging from sparse BLAS operations to advanced direct and iterative sparse solvers
• Working closely with product management and other internal and external partners to understand feature and performance requirements and contribute to the technical roadmaps of libraries
• Finding and realizing opportunities to improve library quality, performance and maintainability through re-architecting and establishing innovative software development practices
Qualifications:
Required:
• PhD or MSc degree (or equivalent experience) in Computational Science and Engineering, Computer Science, Applied Mathematics, or related science or engineering field is preferred
• 5+ years of overall experience in developing, debugging and optimizing high-performance sparse linear algebra software using C++ and parallel programming; ideally using CUDA, MPI, OpenMP, OpenACC, pthreads, or equivalent technologies
• Strong fundamentals in floating point arithmetic and implementation of sparse linear algebra primitives like matrix-vector and matrix-matrix products
• Experience in developing, maintaining, and testing sparse linear algebra libraries
• Strong collaboration, communication, and documentation habits.
Preferred:
• Good knowledge of CPU and/or GPU hardware architecture and low-level GPU performance optimization
• Familiarity with technologies such as multi-frontal factorizations, iterative solvers, preconditioners, and algebraic multigrid
• Experience with adopting and advancing software development practices such as CI/CD systems and project management tools such as JIRA
• Understanding of large-scale computing technologies such as PDE solvers, eigenvalue solvers and time-domain simulation methods (e.g., CFD, FEA)
• Working experience in a globally distributed and agile organization
Company:
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI. Founded in 1993, the company is headquartered in Santa Clara, USA, with a team of 10001+ employees. The company is currently Late Stage.

What Nvidia employees say

Hours and flexibility

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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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