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Pytorch Internship Jobs (NOW HIRING)

We're seeking interns who care about outcomes, think in systems, and make data-driven decisions. If ... Experience with ML libraries, such as TensorFlow, PyTorch, CoreFlow, and Sklearn * Practical ...

We're seeking interns who care about outcomes, think in systems, and make data-driven decisions. If ... Experience with ML libraries, such as TensorFlow, PyTorch, CoreFlow, and Sklearn * Practical ...

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Pytorch Internship information

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How much do pytorch internship jobs pay per hour?

As of Jul 9, 2026, the average hourly pay for pytorch internship in the United States is $17.31, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $19.23 per hour, depending on experience, location, and employer.

What types of projects and collaborative experiences can I expect during a PyTorch Internship?

During a PyTorch Internship, you can expect to work on hands-on machine learning and deep learning projects that involve developing, testing, and optimizing models using the PyTorch framework. Interns often collaborate closely with research scientists, software engineers, and product teams to contribute to real-world applications and open-source initiatives. You may participate in code reviews, brainstorming sessions, and weekly progress meetings, gaining exposure to both independent tasks and team-based problem-solving. This environment fosters both technical growth and communication skills, preparing you for advanced roles in AI and machine learning.

What are the key skills and qualifications needed to thrive as a PyTorch Intern, and why are they important?

To thrive as a PyTorch Intern, you need a solid background in Python programming, machine learning fundamentals, and familiarity with deep learning concepts, typically evidenced by coursework or project experience. Proficiency in PyTorch, version control systems like Git, and tools such as Jupyter Notebooks is highly valued. Strong problem-solving skills, attention to detail, and effective communication help interns contribute meaningfully to team projects and learn quickly. These skills and qualities are crucial for efficiently developing, testing, and deploying machine learning models in a collaborative environment.

What is the difference between Pytorch Internship vs Machine Learning Intern?

AspectPytorch InternshipMachine Learning Intern
Required SkillsProficiency in Pytorch, Python, deep learning conceptsPython, machine learning algorithms, data analysis
Work EnvironmentResearch labs, tech companies, AI startupsTech firms, research institutions, data-driven companies
Industry UsageDeep learning projects, neural network developmentBroader ML applications, data modeling

Both roles involve working with machine learning, but a Pytorch Internship specifically focuses on deep learning frameworks like Pytorch, while a Machine Learning Intern may work across various ML techniques. The Pytorch Internship is ideal for those specializing in neural networks and deep learning, whereas the Machine Learning Intern role covers a wider range of ML applications.

What is a PyTorch internship?

A PyTorch internship is a temporary position, often for students or recent graduates, where individuals gain hands-on experience working with the PyTorch deep learning framework. Interns typically assist with machine learning projects, develop and test models, and contribute to research or product development involving artificial intelligence. These internships provide valuable exposure to real-world applications of AI, opportunities to collaborate with experienced engineers and researchers, and a chance to enhance programming and problem-solving skills. Many internships also offer mentorship and may lead to full-time roles in the field.
More about Pytorch Internship jobs
What cities are hiring for Pytorch Internship jobs? Cities with the most Pytorch Internship job openings:
What are the most commonly searched types of Pytorch jobs? The most popular types of Pytorch jobs are:
What states have the most Pytorch Internship jobs? States with the most job openings for Pytorch Internship jobs include:

Research Internship - United States

Flexion Robotics

San Francisco, CA โ€ข On-site

Full-time, Internship

Vision

Re-posted 27 days ago


Job description

About Flexion:
At Flexion, we're building the intelligence layer powering the next generation of humanoid robots. Our mission is to accelerate the transition from fragile prototypes to real-world humanoid deployment. We are founded by leading scientists in robot reinforcement learning (ex-Nvidia, ex-ETH Zรผrich), and backed by leading international VC firms. In just months, we've gone from our first line of code to deploying real humanoid capabilities.
Fifty of the world's best robotics researchers are already building the future at Flexion's headquarters in Zurich. Among them are Nikita Rudin, David Hoeller, Julian Nubert, and Korrawe Karunratanakul - scientists who have redefined what humanoid robots can do. Now we are building their counterpart team in the United States, in San Francisco.
The Role:
If you are among the most capable and ambitious early-career robotics researchers, someone who has stared at the limits of what robots can do today and decided that simply wasn't good enough, we want to hear from you.
You will join Flexion's US research team as an intern, take on research problems that matter most, and deploy real solutions on real hardware. You will work directly with a world-class team across two continents on challenges that have no published answers yet. This internship is designed to give exceptional graduate researchers the opportunity to do their highest-impact work in a fast-moving industrial research environment, with a clear path to a full-time Research Scientist role following the internship.
Requirements
Must-haves:
  • Ongoing PhD in Robotics, Machine Learning, or a closely related field, or a recently completed Master's degree with exceptional research output
  • Demonstrated experience deploying learning-based controllers on real robotic hardware, or strong research signal that you can do so quickly

Strong working knowledge in:
  • Reinforcement learning
  • Physics-based simulation (Isaac Gym/Lab, MuJoCo, or equivalent)
  • Python and PyTorch, including training neural networks at scale

Knowledge in at least two of the following:
  • Diffusion models
  • Flow matching
  • Dexterous manipulation
  • Sim-to-real transfer and real-to-sim calibration
  • Whole-body control and loco-manipulation
  • Synthetic data generation for robot learning
  • Vision Language Model Fine-Tuning (SFT and RL-based)
  • Transformer-based 3D Scene Understanding

Benefits
  • Competitive compensation package
  • A front-row seat at one of the world's most ambitious robotics companies
  • An energetic, collaborative team with a relentless bias for action
  • The opportunity to build something no one has ever done in this field - alongside the world's leading researchers