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Machine Learning Summer Intern Jobs (NOW HIRING)

Xometry

Machine Learning Intern

Waltham, MA · Hybrid

$27/hr

Xometry's Summer Internship Program offers a unique opportunity to gain hands-on experience and develop essential skills in the manufacturing industry. As a Machine Learning Intern at Xometry, you'll ...

Xometry

Machine Learning Intern

North Bethesda, MD · Hybrid

$27/hr

Xometry's Summer Internship Program offers a unique opportunity to gain hands-on experience and develop essential skills in the manufacturing industry. As a Machine Learning Intern at Xometry, you'll ...

CloudDevs

Machine Learning Intern

Manhattan, NY · Remote

We are looking for a talented Machine Learning Intern to join Optimspace, a leading Information Technology company. As a Machine Learning Intern, you will have the opportunity to work on ...

Veeam Software

AI Intern- Summer 2026

San Jose, CA

$40 - $50/hr

Machine Learning Fundamentals: Strong foundation in supervised/unsupervised learning, optimization, regularization, model evaluation, and deep learning fundamentals. * Model Training Experience:

City of Marco Island, FL

Summer Intern

Marco Island, FL · On-site

$14/hr

Summer Intern positions will begin on June 8, 2026. Requirements for the Program are as follows ... Emphasis is placed on providing varied, meaningful learning experiences to the student, while at ...

Veeam Software

AI Intern- Summer 2026

San Jose, CA · On-site

$40/hr

As a Summer Intern, you will participate in onboarding with the UR team that will set you up for ... Machine Learning Fundamentals: Strong foundation in supervised/unsupervised learning, optimization ...

Veeam Software

AI Intern- Summer 2026

San Jose, CA · On-site

$40/hr

As a Summer Intern, you will participate in onboarding with the UR team that will set you up for ... Machine Learning Fundamentals: Strong foundation in supervised/unsupervised learning, optimization ...

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All JobsMachine Learning Summer Intern Jobs

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.

AI/Machine Learning, Summer Intern (Hybrid)

Accuris

Denver, CO • On-site

$17/hr

Internship

This job post has expired today. Applications are no longer accepted.

Job description

AI/Machine Learning Summer Intern Supply Chain Intelligence | Accuris
Division: Supply Chain Intelligence
Level: Undergraduate (Junior/Senior) or Graduate (MS/MBA)
Location: Denver, CO - Hybrid (3 days on-site per week)
Duration: June 1 - August 3-10, 2026 | 9-10 weeks
Compensation: Paid - $17/hour
ABOUT THE ROLE
Accuris's Supply Chain Intelligence division is transforming how engineers, procurement teams, and sustainability leaders understand the global electronics supply chain. We are looking for a creative, technically strong AI/ML Summer Intern to join our team and help build the next generation of AI-powered capabilities - from carbon footprint calculators for electronic components to predictive algorithms for supply chain risk and availability.
This is a hands-on, build-first internship. You will go from idea to working prototype, collaborating closely with product managers, engineers, and data scientists. By the end of the summer, you will have shipped a real AI tool and presented it to audiences ranging from engineers to senior executives.
WHAT YOU'LL WORK ON
  • Design and build AI-powered prototypes such as carbon footprint calculators for electronic components or predictive models for supply chain risk, demand, and component availability.
  • Apply LLM and generative AI techniques to create intelligent, data-driven tools using platforms like OpenAI, Anthropic Claude, or LangChain.
  • Develop and validate machine learning models using Python and standard ML libraries (scikit-learn, PyTorch, TensorFlow, etc.).
  • Work with cloud-based data pipelines, SQL databases, and dashboards to source and transform supply chain data.
  • Use rapid "vibe coding" methodologies to iterate quickly on AI concepts and validate ideas early.
  • Translate your technical work into clear, compelling presentations for both engineering teams and executive audiences.

WHAT YOU'LL DELIVER
By the end of the summer, you will be expected to deliver two things:
  • A working AI prototype - a functional tool or model that demonstrates clear value against a supply chain intelligence use case (e.g., component carbon footprint estimator, predictive availability scorer, or similar).
  • An executive-ready presentation - a polished deck communicating your approach, methodology, findings, and recommended next steps for the business.

REQUIRED QUALIFICATIONS
  1. Currently enrolled as a Junior or Senior undergraduate, or a Graduate (MS or MBA) student in Computer Science, Data Science, Electrical Engineering, Information Systems, or a related field.
  2. Demonstrated experience building AI applications - whether through coursework, personal projects, open-source contributions, or prior internships.
  3. Proficiency in Python with hands-on experience using ML libraries such as NumPy, Pandas, scikit-learn, PyTorch, or TensorFlow.
  4. Experience working with LLM/GenAI platforms (e.g., OpenAI API, Anthropic Claude, LangChain, RAG pipelines, or prompt engineering).
  5. Familiarity with cloud platforms (AWS, Azure, or GCP) and data tools including SQL and data pipeline or dashboard tooling.
  6. Strong written and verbal communication skills; able to present technical concepts clearly to both technical peers and non-technical stakeholders.
  7. Self-starter with the ability to move fast, iterate, and learn from ambiguous, real-world data problems.

PREFERRED QUALIFICATIONS
  • Prior exposure to supply chain, electronics manufacturing, procurement, or sustainability/ESG domains.
  • Familiarity with carbon accounting frameworks, life cycle assessment (LCA), or sustainability data (e.g., GHG Protocol, Scope 3 emissions).
  • Experience building and evaluating predictive models for time-series, classification, or regression problems.
  • Active portfolio of AI/ML projects (e.g., GitHub, Kaggle, Hugging Face, or personal website).
  • Comfort with rapid prototyping and "vibe coding" - the ability to quickly scaffold and iterate on AI-driven tools.

ABOUT ACCURIS
Accuris provides engineers, procurement specialists, and product teams with trusted data and intelligence to design better products and build more resilient supply chains. Our Supply Chain Intelligence division delivers real-time component data, risk analytics, and predictive insights to help global organizations make faster, smarter sourcing decisions. This internship puts you at the frontier of AI applied to one of the world's most complex and consequential industries.

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