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Undergraduate Machine Learning Internship 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 ...

Hive

Machine Learning Manager

San Francisco, CA

$180K - $250K/yr

Undergraduate or graduate degree in computer science or similar technical field * 4+ years experience as a machine learning engineer, with experience in training large deep learning models and ...

Hive

Machine Learning Manager

Seattle, WA · On-site

$180K - $250K/yr

Undergraduate or graduate degree in computer science or similar technical field * 4+ years experience as a machine learning engineer, with experience in training large deep learning models and ...

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Undergraduate Machine Learning Internship information

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How much do undergraduate machine learning internship jobs pay per year?

As of Jul 3, 2026, the average yearly pay for undergraduate machine learning internship 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 Undergraduate Machine Learning Internship job?

An Undergraduate Machine Learning Internship is a temporary position designed for students pursuing a bachelor's degree who want hands-on experience in machine learning. Interns typically work on real-world projects involving data preprocessing, model development, and performance evaluation under the guidance of experienced engineers or researchers. They may also assist with research, implement algorithms, and optimize models for deployment. The role helps students gain practical skills in coding, data analysis, and machine learning frameworks while preparing them for future careers in AI and data science.

What are the key skills and qualifications needed to thrive in the Undergraduate Machine Learning Internship position, and why are they important?

To thrive as an Undergraduate Machine Learning Intern, you typically need a strong foundation in mathematics, statistics, and programming (Python or R), often supported by ongoing studies in computer science, data science, or a related field. Experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch, and familiarity with data analysis tools are commonly valued. Curiosity, strong problem-solving abilities, and the willingness to work collaboratively in a team make candidates stand out. These skills and qualities are crucial for learning quickly, making meaningful contributions to real projects, and growing in a fast-paced, technical environment.

What types of projects or tasks can I expect to work on during an Undergraduate Machine Learning Internship?

As an Undergraduate Machine Learning Intern, you can expect to assist with tasks such as data preprocessing, model development and evaluation, and implementing machine learning algorithms under the guidance of experienced team members. You may also be involved in cleaning and exploring data sets, creating visualizations, and helping automate parts of the data pipeline. Collaborating with data scientists and engineers, you’ll likely participate in team meetings, code reviews, and brainstorming sessions to address real-world business or research challenges. These hands-on experiences are designed to help you build practical skills and gain exposure to the workflow of professional machine learning projects.

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Undergraduate Machine Learning Internship jobs near you
Machine Learning Internship - PhD: 2027

Machine Learning Internship - PhD: 2027

Susquehanna International Group, LLP

Philadelphia, PA • On-site

Full-time, Internship

Posted 25 days ago

Job description

Overview
Our Machine Learning PhD Internship is a 10-week immersive experience designed for PhD candidates who are passionate about solving high-impact problems at the intersection of data, algorithms, and markets.
As a Machine Learning Intern at Susquehanna, you'll work on high-impact projects that closely reflect the challenges and workflows of our full-time research team. You'll apply your technical expertise in machine learning and data science to real-world financial problems, while developing a deep understanding of how machine learning integrates into Susquehanna's research and trading systems. You will leverage vast and diverse datasets and apply cutting-edge machine learning at scale to drive data-informed decisions in predictive modeling to strategic execution.
What You Can Expect
  • Conduct research and develop ML models to identify patterns in noisy, non-stationary data
  • Work side-by-side with our Machine Learning team on real, impactful problems in quantitative trading and finance, bridging the gap between cutting-edge ML research and practical implementation
  • Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches
  • Design and run experiments using the latest ML tools and frameworks
  • One-on-one mentorship from experienced researchers and technologists
  • Participate in a comprehensive education program with deep dives into Susquehanna's ML, quant, and trading practices
  • Apply rigorous scientific methods to extract signals from complex datasets and shape our understanding of market behavior
  • Explore various aspects of machine learning in quantitative finance from alpha generation and signal processing to model deployment and risk-aware decision making

What we're looking for
  • Currently pursuing a PhD in Computer Science, Machine Learning, Statistics, Physics, Applied Mathematics, or a closely related field
  • Proven experience applying machine learning techniques in a professional or academic setting
  • Strong publication record in top-tier conferences such as NeurIPS, ICML, or ICLR
  • Hands-on experience with machine learning frameworks, including PyTorch and TensorFlow
  • Deep interest in solving complex problems and a drive to innovate in a fast-paced, competitive environment

Why Join Us?
  • Work with a world-class team of researchers and technologists
  • Access to unparalleled financial data and computing resources
  • Opportunity to make a direct impact on trading performance
  • Collaborative, intellectually stimulating environment with global reach

About Susquehanna
Susquehanna is a global quantitative trading firm powered by scientific rigor, curiosity, and innovation. Our culture is intellectually driven and highly collaborative, bringing together researchers, engineers, and traders to design and deploy impactful strategies in our systematic trading environment. To meet the unique challenges of global markets, Susquehanna applies machine learning and advanced quantitative research to vast datasets in order to uncover actionable insights and build effective strategies. By uniting deep market expertise with cutting-edge technology, we excel in solving complex problems and pushing boundaries together.
If you're a recruiting agency and want to partner with us, please reach out to recruiting@sig.com. Any resume or referral submitted in the absence of a signed agreement will not be eligible for an agency fee.

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