Machine Learning Intern Jobs in USA with Visa Sponsorship
Machine Learning Intern roles are among the most actively sponsored positions in the U.S. tech sector, with employers regularly filing H-1B visa and OPT-extension paperwork for strong candidates. Most openings require F-1 status with CPT or OPT authorization, and many convert to full-time sponsored roles. For detailed occupation requirements, see the O*NET profile.
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Get Access To All JobsJob Title: Machine Learning Modeling Winter/Spring Co-Op (Jan-June '27)
Posting Start Date: 10/7/26
Job Location(s): Irvine
If you are looking for a challenging and exciting career in the world of technology, then look no further. Skyworks is an innovator of high-performance analog semiconductors whose solutions are powering the wireless networking revolution. Through our broad technology expertise and one of the most extensive product portfolios in the industry, we are Connecting Everyone and Everything, All the Time.
At Skyworks, you will find a fast-paced environment with a strong focus on global collaboration, minimal layers of management, and the freedom to make meaningful contributions in a setting that encourages creative thinking. We are excited about the opportunity to work with you and glad you want to be part of a team of talented individuals who together are changing the way the world communicates.
Requisition ID: 78575
Description
Skyworks is a global leader in wireless connectivity, delivering cutting-edge RF, acoustic wave, and semiconductor technologies that power next-generation communication systems. As we continue to expand our artificial intelligence and machine learning capabilities, we are leveraging advanced analytics and data-driven approaches to accelerate innovation, optimize manufacturing processes, and enhance product performance.
We are seeking a highly motivated Machine Learning Modeling Engineer Intern to join our Acoustic Device Group. In this role, you will develop, implement, and optimize machine learning models to support the design, analysis, and development of advanced acoustic and RF devices. You will work with complex engineering datasets and collaborate closely with multidisciplinary teams to apply AI and machine learning techniques to real-world semiconductor challenges.
The ideal candidate has strong analytical and problem-solving skills, a solid foundation in machine learning algorithms and data science, and a passion for applying AI technologies to RF, acoustic wave, and semiconductor engineering. This position offers a unique opportunity to contribute to next-generation wireless products while gaining hands-on experience at the intersection of machine learning and advanced semiconductor technology.
Co-Op Period from January to June 2027
Responsibilities
- Apply artificial neural network (ANN) and machine learning techniques to support microwave CAD and semiconductor design projects.
- Develop and evaluate ANN-based models for acoustic devices, electromagnetic (EM) analysis, and parametric modeling.
- Assist in the development of data-driven models for RF filter design and performance prediction.
- Support neural network-based multiphysics modeling of electrical, acoustic, thermal, and mechanical interactions.
- Collect, clean, and preprocess structured, unstructured, time-series, and image datasets for machine learning applications.
- Perform exploratory data analysis (EDA), feature engineering, and data visualization to improve model accuracy and insights.
- Build and optimize LLM-powered agents with capabilities such as tool integration, workflow automation, and multi-step reasoning.
- Research emerging developments in AI, machine learning, and data science, and explore their applications in semiconductor design and manufacturing optimization.
Required Experience and Skills
- Currently pursuing an M.S. or Ph.D. degree in Computer Science, Electrical Engineering, Applied Mathematics, Data Science, or a related technical field.
- Solid foundation in machine learning, deep learning, statistical modeling, and data analysis techniques.
- Proficiency in Python programming; experience with C++ and SQL is a plus.
- Hands-on experience with machine learning frameworks such as PyTorch, TensorFlow, or Keras.
- Familiarity with data analysis and scientific computing libraries, including NumPy, Pandas, and Scikit-learn.
- Basic knowledge of cloud computing platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
- Experience developing machine learning workflows, data pipelines, or scalable software solutions through coursework, research, or projects.
- Strong analytical and problem-solving skills, with attention to detail and the ability to work independently.
- Self-motivated learner with a passion for artificial intelligence, innovation, and continuous professional growth.
Desired Experience and Skills
- Coursework or project experience in large language models (LLMs), generative AI, agent-based systems, or deep learning applications.
- Coursework or project experience in RF, microwave engineering, signal processing, computational electromagnetics, or semiconductor devices.
- Experience working with simulation-generated datasets and physics-based models: knowledge of Physics-Informed Neural Networks (PINNs), surrogate modeling, or digital twin methodologies.
- Familiarity with scientific computing, numerical optimization, and surrogate modeling techniques.
- Familiarity with reinforcement learning, Bayesian optimization, or other optimization techniques for engineering applications.
- Interest in applying AI and machine learning techniques to engineering design automation, semiconductor technologies, and manufacturing optimization.
- Familiarity with Git, Jira, and MLflow for version control and model management.
The typical pay range for an Engineering intern across the U.S. is currently USD $29.00 - $49.00 per hour and for a Non-Engineering intern across the U.S. is currently USD $23.00 - $42.00 per hour. Starting pay will depend on level of education, the ultimate job duties and requirements, and work location. Skyworks has different pay ranges for different work locations in the U.S.
Skyworks is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. Skyworks strives to create an accessible workplace; if you need an accommodation due to a disability, please contact us at accommodations@skyworks.com.
Apply now
Job Title: Machine Learning Modeling Winter/Spring Co-Op (Jan-June '27)
Posting Start Date: 10/7/26
Job Location(s): Irvine
If you are looking for a challenging and exciting career in the world of technology, then look no further. Skyworks is an innovator of high-performance analog semiconductors whose solutions are powering the wireless networking revolution. Through our broad technology expertise and one of the most extensive product portfolios in the industry, we are Connecting Everyone and Everything, All the Time.
At Skyworks, you will find a fast-paced environment with a strong focus on global collaboration, minimal layers of management, and the freedom to make meaningful contributions in a setting that encourages creative thinking. We are excited about the opportunity to work with you and glad you want to be part of a team of talented individuals who together are changing the way the world communicates.
Requisition ID: 78575
Description
Skyworks is a global leader in wireless connectivity, delivering cutting-edge RF, acoustic wave, and semiconductor technologies that power next-generation communication systems. As we continue to expand our artificial intelligence and machine learning capabilities, we are leveraging advanced analytics and data-driven approaches to accelerate innovation, optimize manufacturing processes, and enhance product performance.
We are seeking a highly motivated Machine Learning Modeling Engineer Intern to join our Acoustic Device Group. In this role, you will develop, implement, and optimize machine learning models to support the design, analysis, and development of advanced acoustic and RF devices. You will work with complex engineering datasets and collaborate closely with multidisciplinary teams to apply AI and machine learning techniques to real-world semiconductor challenges.
The ideal candidate has strong analytical and problem-solving skills, a solid foundation in machine learning algorithms and data science, and a passion for applying AI technologies to RF, acoustic wave, and semiconductor engineering. This position offers a unique opportunity to contribute to next-generation wireless products while gaining hands-on experience at the intersection of machine learning and advanced semiconductor technology.
Co-Op Period from January to June 2027
Responsibilities
- Apply artificial neural network (ANN) and machine learning techniques to support microwave CAD and semiconductor design projects.
- Develop and evaluate ANN-based models for acoustic devices, electromagnetic (EM) analysis, and parametric modeling.
- Assist in the development of data-driven models for RF filter design and performance prediction.
- Support neural network-based multiphysics modeling of electrical, acoustic, thermal, and mechanical interactions.
- Collect, clean, and preprocess structured, unstructured, time-series, and image datasets for machine learning applications.
- Perform exploratory data analysis (EDA), feature engineering, and data visualization to improve model accuracy and insights.
- Build and optimize LLM-powered agents with capabilities such as tool integration, workflow automation, and multi-step reasoning.
- Research emerging developments in AI, machine learning, and data science, and explore their applications in semiconductor design and manufacturing optimization.
Required Experience and Skills
- Currently pursuing an M.S. or Ph.D. degree in Computer Science, Electrical Engineering, Applied Mathematics, Data Science, or a related technical field.
- Solid foundation in machine learning, deep learning, statistical modeling, and data analysis techniques.
- Proficiency in Python programming; experience with C++ and SQL is a plus.
- Hands-on experience with machine learning frameworks such as PyTorch, TensorFlow, or Keras.
- Familiarity with data analysis and scientific computing libraries, including NumPy, Pandas, and Scikit-learn.
- Basic knowledge of cloud computing platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
- Experience developing machine learning workflows, data pipelines, or scalable software solutions through coursework, research, or projects.
- Strong analytical and problem-solving skills, with attention to detail and the ability to work independently.
- Self-motivated learner with a passion for artificial intelligence, innovation, and continuous professional growth.
Desired Experience and Skills
- Coursework or project experience in large language models (LLMs), generative AI, agent-based systems, or deep learning applications.
- Coursework or project experience in RF, microwave engineering, signal processing, computational electromagnetics, or semiconductor devices.
- Experience working with simulation-generated datasets and physics-based models: knowledge of Physics-Informed Neural Networks (PINNs), surrogate modeling, or digital twin methodologies.
- Familiarity with scientific computing, numerical optimization, and surrogate modeling techniques.
- Familiarity with reinforcement learning, Bayesian optimization, or other optimization techniques for engineering applications.
- Interest in applying AI and machine learning techniques to engineering design automation, semiconductor technologies, and manufacturing optimization.
- Familiarity with Git, Jira, and MLflow for version control and model management.
The typical pay range for an Engineering intern across the U.S. is currently USD $29.00 - $49.00 per hour and for a Non-Engineering intern across the U.S. is currently USD $23.00 - $42.00 per hour. Starting pay will depend on level of education, the ultimate job duties and requirements, and work location. Skyworks has different pay ranges for different work locations in the U.S.
Skyworks is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. Skyworks strives to create an accessible workplace; if you need an accommodation due to a disability, please contact us at accommodations@skyworks.com.
Apply now
See all 14,496+ Machine Learning Intern Jobs
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Get Access To All JobsTips for Finding Visa Sponsorship as a Machine Learning Intern
Target OPT-friendly employers first
Companies that have filed H-1B petitions for machine learning roles in previous years are your strongest leads. Their willingness to sponsor full-time positions signals they'll support your OPT period and consider future H-1B sponsorship after conversion.
Confirm CPT eligibility before applying
Most ML internships run 10 to 40 hours per week, which affects your CPT authorization. Full-time CPT exceeding 12 months eliminates OPT eligibility entirely, so coordinate with your DSO before accepting any offer involving consecutive full-time summers.
Lead with technical depth, not sponsorship need
Recruiters at ML-heavy companies screen for PyTorch, TensorFlow, and research experience before asking about visa status. Establish your technical fit clearly in applications, then address sponsorship directly only when asked or during offer discussions.
Apply to companies with STEM OPT track records
Employers in computer science, engineering, and data science fields routinely approve STEM OPT extensions, giving you 36 months of work authorization. Prioritize employers whose job descriptions explicitly mention visa sponsorship or have sponsored STEM extensions before.
Use a research publication or project to stand out
Machine learning internships are highly competitive. A published paper, an open-source contribution with real GitHub activity, or a Kaggle competition result gives your application a concrete signal that justifies sponsorship investment from a hiring manager's perspective.
Ask about conversion pathways during the offer stage
Many ML internships convert to full-time roles with H-1B sponsorship. Ask directly whether the company has sponsored H-1B petitions for former interns, and confirm whether your role qualifies as a specialty occupation under their legal team's interpretation.
Frequently Asked Questions
Can international students on F-1 visas work as Machine Learning Interns in the U.S.?
Yes. F-1 students can work as Machine Learning Interns using Curricular Practical Training during their studies or Optional Practical Training after graduation. CPT requires prior DSO authorization and must relate directly to your degree program. OPT gives you up to 12 months of work authorization, with a 24-month STEM extension available for qualifying computer science and engineering degrees, bringing the total to 36 months.
Do Machine Learning Intern roles typically convert to H-1B-sponsored full-time positions?
At larger tech employers, conversion rates from ML intern to full-time sponsored hire are meaningfully high, particularly for candidates who complete a successful internship. Companies including Amazon, Google, and Microsoft have consistent track records of filing H-1B visa petitions for former interns. Smaller startups convert less predictably, so it's worth asking directly during the offer stage whether they've sponsored H-1B petitions for prior interns in machine learning or adjacent engineering roles.
What degree is required for a Machine Learning Internship to qualify for visa sponsorship?
Most ML internship roles require enrollment in or completion of a bachelor's, master's, or PhD program in computer science, data science, electrical engineering, statistics, or a closely related field. For H-1B purposes, the degree must relate specifically to the duties of the role. A general business or liberal arts degree will rarely satisfy the specialty occupation requirement for a machine learning position, even with strong practical experience.
Where can I find Machine Learning Intern jobs that explicitly offer visa sponsorship?
Migrate Mate filters job listings specifically for roles open to visa sponsorship, which saves time compared to sorting through postings that exclude international candidates. Browse ML intern openings on Migrate Mate to find companies that have a demonstrated history of sponsoring F-1 OPT, STEM OPT extensions, and H-1B petitions for engineering and data science roles.
Does full-time CPT during a Machine Learning Internship affect my OPT eligibility?
Yes, and this is a critical detail to get right before accepting an offer. If you accumulate 12 or more months of full-time CPT (20 or more hours per week), you lose your post-completion OPT eligibility entirely. Part-time CPT, regardless of total duration, does not affect OPT. If you're considering multiple back-to-back full-time internships, track your CPT hours carefully with your DSO and consider whether preserving OPT eligibility is strategically more valuable.
What is the prevailing wage requirement for sponsored Machine Learning Intern jobs?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.