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Machine Learning Summer Intern Jobs in New York (NOW HIRING)

Jane Street

Machine Learning Engineer

New York, NY · On-site

Machine learning is a critical pillar of Jane Street's global business. Our ever-changing trading ... The interview process follows the same structure as our Software Engineering Intern interviews ...

Jane Street

Machine Learning Engineer

New York, NY · On-site

Machine learning is a critical pillar of Jane Street's global business. Our ever-changing trading ... The interview process follows the same structure as our Software Engineering Intern interviews ...

Strivector Corp

Machine Learning

Manhattan, NY · On-site

They are seeking a Machine Learning professional capable of tackling research problems with commercial applications, applying technical expertise to real-world financial and operational challenges.

Cushman & Wakefield

Long Island Summer Intern

Melville, NY

$15.50 - $18.50/hr

Job Title Long Island Summer Intern Summary Cushman & Wakefield is a global leader in commercial ... Interns will act as a part of the service line team learning and engaging each step of the way. You ...

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Machine Learning Summer Intern information

See New York salary details

$8

$25

$65

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

As of Aug 11, 2026, the average hourly pay for machine learning summer intern in New York is $25.61, according to ZipRecruiter salary data. Most workers in this role earn between $16.20 and $29.76 per hour, depending on experience, location, and employer.

What types of projects does a machine learning summer intern typically work on?

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 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 are the key skills and qualifications needed to thrive as a machine learning summer intern?

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 is a machine learning summer intern?

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 are the most commonly searched types of Machine Learning Summer jobs in New York? The most popular types of Machine Learning Summer jobs in New York are:
What cities in New York are hiring for Machine Learning Summer Intern jobs? Cities in New York with the most Machine Learning Summer Intern job openings:
Machine Learning Summer Intern jobs near you
Infographic showing various Machine Learning Summer Intern job openings in New York as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 2% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $53,274 per year, or $25.6 per hour.

Machine Learning Engineer

Jane Street

New York, NY • On-site

Full-time

Re-posted 6 days ago

Job description

About the Position
Our goals are to give you a real sense of what it's like to work at Jane Street as a Machine Learning Engineer while also providing a truly unparalleled educational experience. You'll be paired with full-time employees who act as mentors, collaborating with you on real-world ML projects we actually need done. Many classes and activities are shared with our Software Engineering interns, while others focus specifically on machine learning applications and techniques.
Machine learning is a critical pillar of Jane Street's global business. Our ever-changing trading environment serves as a unique, rapid-feedback platform for ML experimentation, allowing us to incorporate new ideas with relatively little friction. If you'd like to learn more, you can have a look at our Machine Learning page.
During the program, you'll work on projects mentored closely by the full-time employees who designed them. Some projects consider big-picture questions that we're still trying to figure out, while others involve building something new. You will get access to our growing GPU cluster containing thousands of H100/H200/B200s and gain an understanding of the differences between textbook machine learning and its application to noisy financial data.
The interview process follows the same structure as our Software Engineering Intern interviews, with one key addition: after your initial technical coding interview over Zoom, you'll have an on-site interview with 2-4 technical rounds, including 1-2 dedicated to assessing ML engineering skills.
Learn more about Jane Street's internship program here.
About You
If you've never thought about a career in finance, you're in good company. Many of us were in the same position before working here. If you have a curious mind, a collaborative spirit, and a passion for solving interesting problems, we have a feeling you'll fit right in. We don't expect you to have a background in finance-we're more interested in how you think and learn than what you currently know. You should be:
  • An undergraduate or PhD student with practical experience training an ML model, working on an ML library, or optimizing an ML workflow
  • A top-notch programmer with a love for technology
  • Intellectually curious, collaborative, and eager to learn
  • Humble and unafraid to ask questions and admit mistakes

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