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Parallel Programming Internship Jobs in Stanford, CA

Apple, Inc.

SW ML Optimization Engineer

Cupertino, CA · On-site

Experience with GPU or parallel programming-e.g., Metal, OpenCL, CUDA, or similar-through coursework, personal projects, internships, or research. Experience with profiling/performance analysis tools ...

Apple

SW ML Optimization Engineer

Cupertino, CA · On-site

Experience with GPU or parallel programming-e.g., Metal, OpenCL, CUDA, or similar-through coursework, personal projects, internships, or research. Experience with profiling/performance analysis tools ...

Apple

SW ML Optimization Engineer

Cupertino, CA

$129K - $225K/yr

  • Medical

  • Dental

  • Retirement

Experience with GPU or parallel programming-e.g., Metal, OpenCL, CUDA, or similar-through coursework, personal projects, internships, or research. Experience with profiling/performance analysis tools ...

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Parallel Programming Internship information

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$10

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$27

How much do parallel programming internship jobs pay per hour?

As of Aug 18, 2026, the average hourly pay for parallel programming internship in Stanford, CA is $20.06, according to ZipRecruiter salary data. Most workers in this role earn between $16.92 and $22.60 per hour, depending on experience, location, and employer.

What is a parallel programming internship?

A Parallel Programming Internship is an opportunity for students or recent graduates to gain hands-on experience in developing software that can execute multiple operations simultaneously. Interns work with technologies such as multi-core processors, GPUs, and distributed computing systems to optimize code for speed and efficiency. These positions are commonly found in industries like scientific research, finance, and tech companies where high-performance computing is crucial. Interns typically gain skills in languages and frameworks like C++, Python, CUDA, OpenMP, and MPI while collaborating with experienced engineers. The experience prepares them for advanced roles in software development and high-performance computing.

What types of projects do interns typically work on during a parallel programming internship?

During a Parallel Programming Internship, interns often contribute to projects involving optimization of existing code, development of parallel algorithms, or performance analysis using multi-core processors or GPUs. You may be tasked with refactoring sequential code to run efficiently on parallel architectures, collaborating with senior engineers, and utilizing frameworks like OpenMP, MPI, or CUDA. These projects provide hands-on experience in solving computational bottlenecks and working closely with cross-functional development teams. This exposure helps build a strong foundation for further roles in high-performance computing or software engineering.

What are the key skills and qualifications needed to thrive as a parallel programming intern, and why are they important?

To thrive as a Parallel Programming Intern, you need a solid understanding of computer science fundamentals, algorithms, and concurrency concepts, often supported by coursework in parallel computing or a related field. Familiarity with programming languages such as C/C++, Python, and parallel computing frameworks like OpenMP, MPI, or CUDA is typically required. Strong analytical thinking, problem-solving ability, and effective teamwork are key soft skills for excelling in collaborative and technical environments. These skills and qualifications are vital for efficiently developing, debugging, and optimizing programs that leverage parallel architectures for improved performance.

What is the difference between Parallel Programming Internship vs Software Development Internship?

AspectParallel Programming InternshipSoftware Development Internship
Required SkillsParallel algorithms, C/C++, CUDA, OpenMPProgramming languages, software design, debugging
Work EnvironmentResearch labs, tech companies focusing on high-performance computingSoftware firms, startups, tech companies
Industry UsageHigh-performance computing, scientific researchWeb, mobile, enterprise applications
Common Search IntentParallel programming, HPC internshipsSoftware development, coding internships

While both internships involve programming skills, a Parallel Programming Internship focuses on high-performance computing and parallel algorithms, often requiring knowledge of C/C++ and GPU programming. In contrast, a Software Development Internship covers broader software engineering skills applicable across various industries. The choice depends on your interest in specialized parallel computing versus general software development.

What job categories do people searching Parallel Programming Internship jobs in Stanford, CA look for?

The top searched job categories for Parallel Programming Internship jobs in Stanford, CA are:

What cities near Stanford, CA are hiring for Parallel Programming Internship jobs?

Cities near Stanford, CA with the most Parallel Programming Internship job openings:

Parallel Programming Internship jobs near you

SW ML Optimization Engineer

Apple, Inc.

Cupertino, CA • On-site

Other

Re-posted 4 days ago

Apple rating

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers

Job description

At Apple, our Platform Architecture group is responsible for connecting our hardware and software into one unified system. You'll collaborate with engineers across Apple to design how all of our technologies work in unison, drive development of our renowned system-on-a-chip architecture and develop forward-looking prototype systems and software.
Description
Our team is driving performance enhancements in application and system software and developing novel algorithms to deliver integrated, highly optimized solutions based on Apple Silicon.
In this role, you will analyze existing and new workloads to identify performance bottlenecks in the hardware and/or software. Working with your colleagues, you will address performance limitations and provide recommendations for Apple hardware and software improvements. In addition to working directly with developers, you will identify patterns of performance challenges on Apple silicon, emerging new usage models, and provide feedback to the silicon and software teams for potential improvements.
Minimum Qualifications
Bachelor's degree in Computer Science, Computer Engineering, Mathematics, Electrical Engineering, or a related quantitative field (or equivalent practical experience).
Experience with GPU or parallel programming-e.g., Metal, OpenCL, CUDA, or similar-through coursework, personal projects, internships, or research.
Experience with profiling/performance analysis tools (e.g., Xcode Instruments, VTune, Nsight Compute, or equivalent) and basic performance analysis concepts.
Development experience in Python, C or C++.
Preferred Qualifications
Solid foundation in mathematics, algorithms, and/or computer architecture fundamentals.
Experience writing or tuning compute kernels (e.g., GEMM, attention, or other numerically intensive routines).
Exposure to ML frameworks such as PyTorch, and to AI/ML, graphics, or HPC workloads and benchmarks.
Coursework or projects involving parallel computing, numerical methods, signal processing, or performance optimization.
Interest in (or exposure to) the deeper stack - drivers, firmware, compilers, or low-level libraries.
Interest in Apple Silicon and its frameworks (Metal, MLX, Core ML).
Curiosity about hardware/software co-design and a demonstrated drive to learn independently.
Strong communication skills and the ability to collaborate effectively across teams.

What Apple employees say

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

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