Jobs
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:
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Shape how careers evolve in the AI economy at global scale, with visible real-world impact
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Work directly with leading AI labs, Fortune 500 partners, and top educational institutions
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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:
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May 18 – August 7, 2026
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June 15 – September 4, 2026
IN THIS ROLE, YOU WILL:
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Partner with senior engineers and data scientists to develop machine learning models that improve user experience
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Build Agentic pipelines/workflows to improve the Handshake student/employer user experience
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Contribute to experimentation, model evaluation, and performance monitoring
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Participate in technical discussions, brainstorming sessions, and team reviews
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Document methodologies and findings to support knowledge sharing and long-term system improvements
YOU HAVE
Must Haves:
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Are currently pursuing a degree in Computer Science, Data Science, or a related field
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Have strong programming skills in Python and experience with ML frameworks such as Py Torch or Tensor Flow
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Have exposure to software engineering best practices (version control, testing, code reviews)
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Have familiarity with data analysis techniques and experience with SQL
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Have strong problem-solving skills and the ability to work in a collaborative team environment
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Have strong communication skills and are able to explain technical concepts effectively
Bonus Points:
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Experience with cloud platforms such as AWS, Google Cloud, or Azure
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Experience with modern coding tools like Cursor/Claude code/Codex
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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.)
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💰 Competitive hourly compensation
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📚 Mentorship and hands-on learning from experienced ML engineers
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💻 5 days/week in-office experience
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🤝 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
Series EHandshake 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
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