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Internship Research Assistant Machine Learning Jobs

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 ...

Since the team works closely with trading floor personnel to assist with portfolio management ... internships, undergraduate research or thesis, or substantial independent technical projects ...

New

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 ...

We have an opening for Machine Learning Research experts to join our team and advance the discipline as well as apply cutting edge tools and techniques to some of society's most important problems.

We have an opening for Machine Learning Research experts to join our team and advance the discipline as well as apply cutting edge tools and techniques to some of society's most important problems.

We have an opening for Machine Learning Research experts to join our team and advance the discipline as well as apply cutting edge tools and techniques to some of society's most important problems.

Machine Learning Analyst

Boston, MA · On-site

$110K - $145K/yr

Since the team works closely with trading floor personnel to assist with portfolio management ... internships, undergraduate research or thesis, or substantial independent technical projects ...

New

We are an Applied ML team pushing the limits of question answering, assistant response ranking ... As part of this group, you will be doing large scale machine learning and deep learning research ...

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Internship Research Assistant Machine Learning information

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How much do internship research assistant machine learning jobs pay per hour?

As of Jul 21, 2026, the average hourly pay for internship research assistant machine learning in the United States is $19.33, according to ZipRecruiter salary data. Most workers in this role earn between $14.90 and $23.08 per hour, depending on experience, location, and employer.

What is the difference between Internship Research Assistant Machine Learning vs Research Assistant Data Science?

AspectInternship Research Assistant Machine LearningResearch Assistant Data Science
Required CredentialsUndergraduate or graduate in CS, AI, or related fieldsUndergraduate or graduate in CS, Statistics, or related fields
Work EnvironmentAcademic labs, research institutions, tech companiesAcademic institutions, research centers, industry
Employer & Industry UsageUniversities, research firms, tech companies focusing on AI/MLUniversities, research organizations, data-driven industries
Common Search & ComparisonYesYes

The Internship Research Assistant Machine Learning and Research Assistant Data Science roles share similarities in educational background and work environments. However, the Machine Learning position emphasizes AI and ML-specific skills, while Data Science focuses more on statistical analysis and data management. Both roles are common in academic and industry settings, often compared by students and professionals exploring research opportunities in data-driven fields.

More about Internship Research Assistant Machine Learning jobs
What cities are hiring for Internship Research Assistant Machine Learning jobs? Cities with the most Internship Research Assistant Machine Learning job openings:
What states have the most Internship Research Assistant Machine Learning jobs? States with the most job openings for Internship Research Assistant Machine Learning jobs include:
Infographic showing various Internship Research Assistant Machine Learning job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, 1% Temporary, and 2% Contract. Highlights an 99% Physical, and 1% Remote job distribution, with an average salary of $40,200 per year, or $19.3 per hour.
Machine Learning Engineer

Machine Learning Engineer

Jane Street

New York, NY • On-site

Full-time

Re-posted 14 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