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Internship Gpu Jobs (NOW HIRING)

Modal, Inc

ML Research Intern

New York, NY · On-site

They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it ... This internship is well suited to candidates interested in improving existing methods and ...

Samsung Semiconductor, Inc.

Engineer

San Jose, CA

$160K - $208K/yr

Design and document major units in a GPU pipeline targeted at mobile graphics and machine learning ... Completion of a graduate level course, research project, or internship involving the following: 1. ...

Samsung Electronics Co., Ltd.

Engineer

San Jose, CA · On-site

$160K - $208K/yr

Design and document major units in a GPU pipeline targeted at mobile graphics and machine learning ... Completion of a graduate level course, research project, or internship involving the following: 1. ...

Atoms

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144K - $190K/yr

... GPU boundaries. • Experience with modern deep learning frameworks (PyTorch or JAX) and runtime compilation. • Robust programming skills in Python and C++. • 4+ years of non-internship ...

Atoms

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144K - $190K/yr

... GPU boundaries. • Experience with modern deep learning frameworks (PyTorch or JAX) and runtime compilation. • Robust programming skills in Python and C++. • 4+ years of non-internship ...

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How much do internship gpu jobs pay per hour?

As of Aug 11, 2026, the average hourly pay for internship gpu in the United States is $15.54, according to ZipRecruiter salary data. Most workers in this role earn between $12.50 and $17.55 per hour, depending on experience, location, and employer.

What is the difference between Internship Gpu vs GPU Engineer?

AspectInternship GpuGPU Engineer
Required CredentialsEnrolled in or recent graduate of Computer Science or related fieldBachelor's or Master's in Computer Science, Electrical Engineering, or related
Work EnvironmentInternship programs, entry-level tasks, learning-focusedFull-time, professional environment, design and optimization of GPU hardware/software
Employer & Industry UsageTech companies, research labs, internships for skill developmentTech companies, hardware manufacturers, industry standard role

In summary, an Internship Gpu is a temporary, learning-focused position for students or recent graduates, while a GPU Engineer is a full-time professional responsible for designing and developing GPU hardware and software. The internship provides foundational experience, whereas the engineer role involves advanced technical responsibilities.

More about Internship Gpu jobs
What cities are hiring for Internship Gpu jobs? Cities with the most Internship Gpu job openings:
What are the most commonly searched types of Gpu jobs? The most popular types of Gpu jobs are:
What states have the most Internship Gpu jobs? States with the most job openings for Internship Gpu jobs include:
What job categories do people searching Internship Gpu jobs look for? The top searched job categories for Internship Gpu jobs are:
Internship Gpu jobs near you
Infographic showing various Internship Gpu job openings in the United States as of August 2026, with employment types broken down into 12% Internship, 63% Full Time, 22% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $32,333 per year, or $15.5 per hour.

ML Research Intern

Modal, Inc

New York, NY • On-site

Full-time

Posted 13 days ago

Job description

About Us:
AI needs a new infrastructure layer. We're building it at Modal.
Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now.
Our customers include category-defining companies like Lovable, Ramp, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale.
We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September.
Our team includes creators of popular open-source projects (e.g.,Seaborn,Luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.
The Role:
We are looking for PhD research interns with strong research experience in reinforcement learning, machine learning, and foundation models, including large language and multimodal models, to join our research team. This internship is well suited to candidates interested in improving existing methods and developing new techniques for large-scale model training, optimization, and inference, extending models to long-context and long-horizon tasks, and improving inference-time efficiency, reliability, and robustness in high-stakes real-world deployments.
Preferred Qualifications:
  1. Currently pursuing a PhD in computer science, machine learning, or a related field.
  2. A demonstrated record of research in reinforcement learning, machine learning, foundation models, or related areas.
  3. Experience developing and evaluating large-scale models or machine learning systems.
  4. Familiarity with distributed training, large-scale inference, or multi-GPU environments.
  5. Publications at leading venues such as NeurIPS, ICML, ICLR, CVPR, CoRL, UAI, JMLR, or TMLR.
  6. Strong programming and engineering skills, with the ability to translate research ideas into working implementations.
  7. A collaborative, mission-driven mindset and the ability to work effectively across research and engineering teams.

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