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Internship Machine Learning Visa Sponsorship Jobs

Chefman

Machine Learning Engineer

Mahwah, NJ · On-site

As a Machine Learning Engineer, you will play a critical role in shaping the future of cooking ... Chefman is unable to provide visa sponsorship for this position. Candidates must be legally ...

Advatix Inc.

Machine Learning Engineer

San Mateo, CA · On-site

$110 - $165/hr

Machine Learning Engineer / Research Engineer Pay: $$110,000 - $165,000 Base Salary + Equity Shift ... San Mateo, CA (Peninsula) - Onsite Preferred Schedule: Full time, Permanent Role Visa Sponsorship:

Poesis

Machine Learning Engineer

San Francisco, CA · On-site

$200K - $280K/yr

About the Role At Poesis, machine learning and artificial intelligence open the door to improved ... Current legal authorization to work in the US required; continuing work visa sponsorship available ...

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Internship Machine Learning Visa Sponsorship information

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How much do internship machine learning visa sponsorship jobs pay per year?

As of Aug 20, 2026, the average yearly pay for internship machine learning visa sponsorship in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What is an internship in machine learning with visa sponsorship?

An internship in machine learning with visa sponsorship is a temporary position offered by a company or institution to students or recent graduates who want to gain hands-on experience in machine learning, while also supporting their legal authorization to work in a country where they are not citizens or permanent residents. These internships typically involve working on real-world machine learning projects, collaborating with experienced professionals, and receiving mentorship. Visa sponsorship means the employer assists the intern in obtaining the necessary visa or work permit, such as an F-1 CPT/OPT in the US or a Tier 5 in the UK, so they can legally participate in the internship.

What types of projects do interns typically work on during a machine learning internship with visa sponsorship?

Interns in Machine Learning roles with visa sponsorship often contribute to real-world projects such as data preprocessing, developing and testing machine learning models, and assisting with research to improve algorithms. You may collaborate closely with data scientists, software engineers, and product teams to deploy models or analyze results. This hands-on work provides valuable exposure to industry-standard tools and practices, while also offering networking opportunities and mentorship. Such internships are structured to give you meaningful tasks that contribute to the team's goals and your professional growth.

What are the key skills and qualifications needed to thrive as a machine learning intern with visa sponsorship?

To thrive as a Machine Learning Intern, you generally need a solid background in computer science, statistics, and mathematics, often supported by coursework or a degree in a related field. Familiarity with programming languages like Python or R, experience with machine learning libraries (such as TensorFlow, PyTorch, or scikit-learn), and exposure to data handling tools are typically expected. Strong analytical thinking, problem-solving abilities, and clear communication skills help interns collaborate effectively and learn quickly in diverse teams. These skills are essential for contributing meaningfully to projects, adapting to new challenges, and succeeding in a global, fast-paced work environment.

Do interns need visa sponsorship?

Interns in machine learning roles often require visa sponsorship if they are international students or non-citizens seeking work authorization. Employers typically sponsor visas such as the J-1 or H-3 for internship programs, and candidates should verify specific visa requirements based on their nationality and the internship location. Having relevant skills in programming, data analysis, and machine learning tools can support the sponsorship process.
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Internship Machine Learning Visa Sponsorship jobs near you
Infographic showing various Internship Machine Learning Visa Sponsorship job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Internship - Machine Learning Engineer

Smule

Salt Lake City, UT • Remote

Other

Re-posted 18 days ago

Job description

Smule has been on a mission to bring the world together through music since 2008. Music is much more than listening… it's about creating, sharing, discovering, participating, and connecting with people. With dozens of millions of monthly active users creating over 20 million songs every day, Smule is connecting people all over the world through the joy of making music and transforming the music landscape from one of passive listening to collaborative creative expression and active engagement.


About the Role:

We are looking for a Machine Learning Engineer to own the end-to-end lifecycle of ML models in production at Smule, from training and optimization through deployment, monitoring, and iteration. You will work closely with research scientists to bring models off the bench and into scalable, reliable systems that serve millions of users. The ideal candidate is a strong engineer first, with deep practical knowledge of ML systems, a passion for reliability, and an eye for performance.


We strongly encourage candidates with non-traditional backgrounds to apply. If your path into ML engineering came through backend systems, DevOps, audio software, data engineering, or another field, we want to hear from you.


What You'll Be Doing:

  • Design, build, and maintain production ML pipelines encompassing data ingestion, feature engineering, model training, evaluation, and deployment.
  • Optimize models for production constraints including latency, throughput, memory footprint, and cost, using techniques such as quantization, distillation, pruning, and efficient serving architectures.
  • Implement robust monitoring, alerting, and observability for deployed models, covering data drift, prediction quality, and system health.
  • Collaborate with research scientists to integrate new model architectures and training techniques into production systems with minimal friction.
  • Build and improve CI/CD pipelines for ML, including automated testing, validation gates, and staged rollouts.
  • Manage compute infrastructure and costs, making informed tradeoffs between performance, reliability, and budget.


What We're Looking For:

  • Degree (B.S., M.S., or Ph.D.) in Computer Science, Software Engineering, Electrical Engineering, or a related technical discipline, or currently pursuing one.
  • Strong proficiency in Python and experience with deep learning serving (TorchServe, Triton, vLLM, or equivalent).
  • Solid understanding of systems engineering: networking, storage, containerization, orchestration, and monitoring.
  • Ability to reason about tradeoffs between latency, throughput, cost, and model quality.


Bonus Points For:

  • Experience serving large language models or other generative models at scale.
  • Familiarity with audio/music processing pipelines and real-time inference constraints.
  • Experience with Bayesian optimization, bandit algorithms, or adaptive experimentation platforms.
  • Contributions to open-source ML infrastructure projects.


Smule is an Equal Opportunity Employer and considers all qualified applicants without regard to race, color, religion, sex, gender identity or expression, sexual orientation, national origin, ancestry, age, disability, medical condition, genetic information, marital status, military or veteran status, or any other protected characteristic under federal, state, or local law.


We are committed to creating an inclusive environment for all employees and applicants. If you require a reasonable accommodation during the application or interview process, please let us know.