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Machine Learning Summer Intern Jobs (NOW HIRING)

Aivra Health LLC

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range: $28 - $45 per hour Visa: H1B Sponsorship Available | STEM OPT, OPT & CPT Candidates Welcome Position ...

Aivra Health LLC

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range: $28 - $45 per hour Visa: H1B Sponsorship Available | STEM OPT, OPT & CPT Candidates Welcome Position ...

Pravāh

ML Summer Intern

San Francisco, CA · On-site

$5K - $10K/mo

We apply modern machine learning to complex physical infrastructure problems spanning grid ... a summer internship. As an ML Intern at Pravah, you will work on real, open-ended technical ...

USCS

Data Analytics Summer Intern

Camden, NJ · On-site

$20/hr

Data Analytics Summer Intern (3 Months) Who We Are : USCS is driven to advance, innovate and serve ... Shadow data scientists and assist on tasks related to machine learning projects (e.g., labeling ...

Louisiana Empowerment

Summer Intern

Baton Rouge, LA · On-site

$11.75 - $14.25/hr

... based summer camp setting. As an intern, you won't just be "helping out"you will be on the front ... learning activities to help youth develop healthy coping mechanisms. * Case Management Support:

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Machine Learning Summer Intern information

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$25.5K

$42.6K

$88K

How much do machine learning summer intern jobs pay per year?

As of May 28, 2026, the average yearly pay for machine learning summer intern 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 are the key skills and qualifications needed to thrive as a Machine Learning Summer Intern, and why are they important?

To thrive as a Machine Learning Summer Intern, you need a solid understanding of programming (especially Python), foundational knowledge of machine learning concepts, and coursework or experience in statistics and mathematics. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is typically expected. Strong problem-solving abilities, eagerness to learn, and effective communication skills help you collaborate and adapt in a fast-paced research or development setting. These abilities are crucial for contributing to real-world projects, learning from experienced mentors, and building a foundation for a future career in machine learning.

What types of projects do Machine Learning Summer Interns typically work on, and how do these contribute to the team's goals?

Machine Learning Summer Interns often work on focused projects such as data preprocessing, developing and testing machine learning models, or contributing to research and prototyping efforts. These projects are designed to provide practical experience while directly supporting the team's ongoing initiatives, such as improving model accuracy or automating data pipelines. Interns usually collaborate closely with data scientists and engineers, gaining mentorship and exposure to real-world problem-solving. This hands-on involvement helps interns understand the end-to-end process of deploying machine learning solutions and prepares them for future roles in the field.

What are Machine Learning Summer Interns?

Machine Learning Summer Interns are students or recent graduates who work temporarily at a company, usually during the summer, to gain practical experience in machine learning. They typically assist with data analysis, model development, and research tasks under the supervision of experienced data scientists or engineers. This role allows interns to apply their academic knowledge to real-world problems, learn industry tools and workflows, and build professional networks. Internships often serve as a stepping stone to full-time positions in machine learning or related fields.

What is the difference between Machine Learning Summer Intern vs Data Science Summer Intern?

AspectMachine Learning Summer InternData Science Summer Intern
Required CredentialsUndergraduate or graduate in CS, AI, or related fields; some experience in ML frameworksUndergraduate or graduate in statistics, CS, or related fields; experience in data analysis
Work EnvironmentDeveloping ML models, algorithms, and prototypes in tech or research companiesAnalyzing datasets, creating reports, and supporting data-driven decisions in various industries
Employer & Industry UsageTech companies, AI startups, research labsFinance, healthcare, marketing, and tech firms

While both roles involve working with data, Machine Learning Summer Interns focus on developing algorithms and models, whereas Data Science Summer Interns analyze data to generate insights. The roles often overlap but differ mainly in technical focus and project scope.

What cities are hiring for Machine Learning Summer Intern jobs? Cities with the most Machine Learning Summer Intern job openings:
What are the most commonly searched types of Machine Learning Summer jobs? The most popular types of Machine Learning Summer jobs are:
What states have the most Machine Learning Summer Intern jobs? States with the most job openings for Machine Learning Summer Intern jobs include:
Machine Learning Summer Intern jobs near you
Infographic showing various Machine Learning Summer Intern job openings in the United States as of May 2026, with employment types broken down into 49% Full Time, 27% Part Time, 2% Temporary, and 22% Contract. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.
Machine Learning Engineering Intern

Machine Learning Engineering Intern

Qeexo, Co.

San Clemente, CA • On-site

$25/hr

Full-time

Posted 13 days ago

Job description

Machine Learning Engineer Intern TDK SensEI San Clemente, CA
This position is for our San Clemente, CA office - only apply if you are based there or willing to relocate
At TDK SensEI, we are transforming how industrial customers utilize and interact with sensor data. We specialize in developing advanced AI solutions capable of running directly on edge devices. By processing data locally, TDK SensEI enhances real-time decision-making, privacy, security, and cost efficiency. Our offerings include automated machine learning tools, AI-powered condition-based monitoring systems, and various sensor devices optimized for low latency and power consumption. Collaborating with leading global companies, we empower teams to effortlessly devise and implement machine learning solutions for industrial applications, all without the need for coding.
We are looking for a machine learning intern who loves working with sensor data, loves developing novel algorithms, and has strong curiosity about developing new GenAI-based ML applications. You will be working with a highly capable team of machine learning engineers and software engineers and will have the opportunity to make a meaningful impact on important new product development.
As a Machine Learning Engineer Intern, your responsibilities will include:
1. Assist in Model Development: Collaborate with senior engineers to develop and train machine learning models tailored for edge devices.
2. Data Collection and Preprocessing: Gather and preprocess data from various sensors and sources to ensure high-quality inputs for AI models.
3. Prototype Development: Develop and test prototypes for new Gen AI-based use cases, ensuring they meet performance and reliability standards.
4. Performance Evaluation: Conduct experiments to evaluate the performance of AI models and edge solutions, identifying areas for improvement.
5. Collaboration: Work closely with cross-functional teams, including machine learning and software engineers, to integrate AI solutions into prototype systems.
Ideal Candidate
. Signal processing and machine learning (most likely in EE major)
. Computer vision (most likely in CS major)
. Language model (most likely in CS major)
• Deep knowledge of statistical and machine learning approaches and problem domains
• Machine Learning/Computer Science/Electrical Engineering background with strong coding ability and proficiency with Python or other OOP language
• Proven success with multiple ML/AI/classification projects (research papers, open-source implementations, etc.)
• Expertise in one or more specific areas of research: automated machine learning, anomaly detection, condition monitoring, predictive maintenance, neural nets, deep learning, signal processing, digital imaging, ensemble learning, and system identification
• Experience working with GenAI applications
• Comfortable working in a terminal environment, writing scripts (Bash/Python) to process data and implement algorithms
Skills & Requirements:
• Master's or PhD student
• Python or other modern OOP language (proficient)
• Data Structures and Algorithms (proficient)
• Deep Learning (proficient)
• Data Structures and Algorithms (familiar)
• Experience with Docker and AWS (familiar)
• US Work Authorization required
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About Qeexo

Sourced by ZipRecruiter

Industry

It services

Company size

1 - 10 Employees

Headquarters location

Mountain View, CA, US

Year founded

2012

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