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JobsHandshake

AI/Machine Learning Engineer Intern

Handshake

AI/Machine Learning Engineer Intern

Handshake

San Francisco, CA

·

On-site

·

Internship

·

1w ago

ABOUT HANDSHAKE

Handshake is the career network for the AI economy. More than 20 million knowledge workers, 1,600 educational institutions, and 1 million employers — including 100% of the Fortune 50 — trust Handshake to power career discovery, hiring, and upskilling. From freelance AI training gigs to first internships to full-time careers and beyond, we connect talent with opportunity at every stage.

This unique position in the ecosystem is driving exceptional growth — in 2025, we tripled ARR at scale.

Why join Handshake now:

  • Shape how careers evolve in the AI economy at global scale, with visible real-world impact

  • Work directly with leading AI labs, Fortune 500 partners, and top educational institutions

  • Help build a rapidly scaling business on a path toward multi-billion-dollar revenue

THE ROLE:

As a AI/Machine Learning Engineering Intern, you will contribute to building intelligent product experiences that help students discover and secure opportunities. Your work will span search, recommendations, matching, and other discovery systems that power job exploration on Handshake.

You will gain hands-on experience developing, evaluating, and deploying machine learning models in a production environment, learning how large-scale ML systems are designed, optimized, and maintained.

This is a paid, full-time summer internship with two cohort options:

  • May 18 – August 7, 2026

  • June 15 – September 4, 2026

IN THIS ROLE, YOU WILL:

  • Partner with senior engineers and data scientists to develop machine learning models that improve user experience

  • Build Agentic pipelines/workflows to improve the Handshake student/employer user experience

  • Contribute to experimentation, model evaluation, and performance monitoring

  • Participate in technical discussions, brainstorming sessions, and team reviews

  • Document methodologies and findings to support knowledge sharing and long-term system improvements

YOU HAVE

Must Haves:

  • Are currently pursuing a degree in Computer Science, Data Science, or a related field

  • Have strong programming skills in Python and experience with ML frameworks such as Py Torch or Tensor Flow

  • Have exposure to software engineering best practices (version control, testing, code reviews)

  • Have familiarity with data analysis techniques and experience with SQL

  • Have strong problem-solving skills and the ability to work in a collaborative team environment

  • Have strong communication skills and are able to explain technical concepts effectively

Bonus Points:

  • Experience with cloud platforms such as AWS, Google Cloud, or Azure

  • Experience with modern coding tools like Cursor/Claude code/Codex

  • Prior internship or project experience in applied machine learning in domains such as NLP, search and recommendation systems

WE OFFER

Handshake provides benefits that help you feel supported and thrive at work and in life.
(The below benefits apply to US-based interns.)

  • 💰 Competitive hourly compensation

  • 📚 Mentorship and hands-on learning from experienced ML engineers

  • 💻 5 days/week in-office experience

  • 🤝 Structured intern programming and team events

Explore our mission, values, and open roles at joinhandshake.com/careers http://joinhandshake.com/careers.

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About Handshake

Handshake

Handshake

Series E

Handshake is a career services platform that connects college students and recent graduates with employers for job opportunities and recruiting.

501-1,000

Employees

San Francisco

Headquarters

$3.5B

Valuation

Reviews

3.7

1 reviews

Work Life Balance

3.0

Compensation

3.0

Culture

3.0

Career

2.5

Management

3.0

25%

Recommend to a Friend

Pros

Platform available for job applications

Cons

Difficulty finding jobs

Low success rate after many applications

Salary Ranges

6 data points

Mid/L4

Mid/L4 · Goods In Team Leader and Stock Controller

1 reports

-

total / year

Base

-

Stock

-

Bonus

-

Interview Experience

5 interviews

Difficulty

3.2

/ 5

Duration

14-28 weeks

Offer Rate

60%

Experience

Positive 60%

Neutral 0%

Negative 40%

Interview Process

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Onsite/Virtual Interviews

5

Final Interview

6

Offer

Common Questions

Technical Knowledge

Behavioral/STAR

Coding/Algorithm

Past Experience

Culture Fit