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Applied Math Internships Jobs (NOW HIRING)

Nvidia

$104K - $143K/yr

... interns. * Working closely with product management and other internal and external customers to ... PhD, Master's, or Bachelor's degree in Computer Science, Applied Math, or related science or ...

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How much do applied math internships jobs pay per year?

As of Jul 24, 2026, the average yearly pay for applied math internships in the United States is $58,837.00, according to ZipRecruiter salary data. Most workers in this role earn between $45,000.00 and $70,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in Applied Math Internships, and why are they important?

To thrive in Applied Math Internships, you need strong mathematical reasoning, problem-solving abilities, and coursework in calculus, linear algebra, and statistics. Familiarity with programming languages like Python, MATLAB, or R, as well as data analysis tools, is often required. Effective communication, collaboration, and adaptability help interns present findings and work within interdisciplinary teams. These skills and qualities are essential for translating mathematical theory into practical solutions and contributing effectively to research or business projects.

What is the difference between Applied Math Internships vs Data Analyst Internships?

AspectApplied Math InternshipsData Analyst Internships
Required CredentialsMathematics, statistics, or related degrees; programming skillsStatistics, data analysis, programming, often with business focus
Work EnvironmentResearch labs, tech companies, finance, academiaBusiness, finance, marketing, tech firms
Employer & Industry UsageResearch institutions, tech companies, finance firmsCorporations, consulting firms, marketing agencies
Common Search & Comparison IntentUnderstanding internship roles in applied mathExploring data analysis internship opportunities

Applied Math Internships focus on mathematical modeling, algorithm development, and research, often in academic or research settings. Data Analyst Internships emphasize data interpretation, visualization, and business insights, typically within corporate environments. While both roles require analytical skills and programming knowledge, they serve different industry needs and career paths.

What types of projects can I expect to work on during an Applied Math internship?

As an Applied Math intern, you’ll typically work on real-world problems that require mathematical modeling, data analysis, and algorithm development. Projects may include optimizing business processes, analyzing large datasets, or developing simulations for engineering or financial applications. Interns often collaborate with interdisciplinary teams that include data scientists, engineers, and business analysts, giving you exposure to practical applications of mathematical theories. This hands-on experience helps build both technical and communication skills, which are valuable for future career growth.

What are applied math internships?

Applied math internships are short-term opportunities for students or recent graduates to gain practical experience using mathematical theories and methods to solve real-world problems in various industries. These internships often involve working on projects related to data analysis, modeling, optimization, or statistical research. They provide valuable hands-on experience, help build professional networks, and can be a stepping stone to a full-time career in fields like finance, technology, engineering, or research. Interns typically collaborate with professionals, learn new software tools, and apply classroom knowledge to practical challenges.
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Applied Math Internships jobs near you
Infographic showing various Applied Math Internships job openings in the United States as of July 2026, with employment types broken down into 75% Full Time, 24% Part Time, and 1% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $58,837 per year, or $28.3 per hour.
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

Posted 10 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

5th of 217 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.

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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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