Job Overview
Location
San Francisco, California, USA
Job Type
Full-time
Category
Machine Learning Engineer
Date Posted
February 27, 2026
Full Job Description
đź“‹ Description
- • As a Machine Learning Engineering Intern at Handshake, you will play a pivotal role in shaping the future of career discovery within the burgeoning AI economy. You will be instrumental in developing and refining intelligent product experiences that empower students to uncover and secure meaningful opportunities. Your contributions will directly impact core functionalities such as search, recommendations, matching algorithms, and other critical discovery systems that form the backbone of the Handshake platform. This internship offers a unique opportunity to gain invaluable, hands-on experience in the end-to-end lifecycle of machine learning models, from initial development and rigorous evaluation to seamless deployment within a dynamic production environment.
- • You will delve deep into the intricacies of how large-scale machine learning systems are architected, meticulously optimized for performance, and consistently maintained to ensure reliability and scalability. This immersive experience will provide a comprehensive understanding of the challenges and best practices involved in building and operating ML systems at scale, preparing you for future roles in this rapidly evolving field.
- • This is a paid, full-time summer internship designed to provide a rich learning and development experience. We offer two distinct cohort options to accommodate academic schedules: the first runs from May 18 to August 7, 2026, and the second from June 15 to September 4, 2026. Both cohorts provide an intensive, project-focused period.
- • In this role, you will actively partner with seasoned senior engineers and data scientists, collaborating closely on the design and implementation of sophisticated machine learning models. Your work will focus on enhancing key product features and elevating the overall user experience for millions of students and employers.
- • You will be deeply involved in the experimentation process, contributing to the design of A/B tests, the rigorous evaluation of model performance against defined metrics, and the continuous monitoring of deployed models to ensure they are performing optimally and meeting business objectives.
- • Your participation will extend to technical discussions, where you will share insights, contribute to brainstorming sessions for new features and model improvements, and engage in constructive team reviews of code, methodologies, and results.
- • A crucial aspect of this internship is the documentation of your methodologies, findings, and any challenges encountered. This ensures robust knowledge sharing within the team and contributes to the long-term maintainability and improvement of our ML systems.
- • You will gain exposure to the full software development lifecycle within an ML context, including version control using Git, writing unit and integration tests for ML components, and participating in code reviews to maintain high code quality and foster collaborative development.
- • The role requires a strong analytical mindset, enabling you to dissect complex problems, propose innovative solutions, and critically assess the impact of your work on user engagement and business outcomes.
- • You will have the opportunity to work with cutting-edge technologies and contribute to a product that is making a tangible difference in the lives of students and the hiring landscape for businesses, all within the exciting domain of AI-driven career services.
- • This internship is an exceptional chance to build a strong portfolio of applied ML projects, gain mentorship from industry leaders, and understand the practical application of academic research in a real-world, high-growth technology company.
- • You will contribute to building a rapidly scaling business on a path toward multi-billion-dollar revenue, directly impacting how careers evolve in the AI economy at a global scale, with visible real-world impact.
- • Work directly with leading AI labs, Fortune 500 partners, and top educational institutions, gaining exposure to diverse perspectives and cutting-edge industry practices.
- • Help build a rapidly scaling business on a path toward multi-billion-dollar revenue, contributing to Handshake's significant growth trajectory.
🎯 Requirements
- • Currently pursuing a Doctorate degree in Computer Science, Data Science, or a closely related quantitative field.
- • Demonstrated experience in supervised and/or unsupervised machine learning techniques, with a foundational understanding of ML operations (MLOps) principles.
- • Strong programming proficiency in Python, coupled with practical experience using major ML frameworks such as PyTorch or TensorFlow.
- • Familiarity with software engineering best practices, including version control (e.g., Git), automated testing, and code review processes.
- • Solid understanding of data analysis techniques and practical experience with SQL for data querying and manipulation.
- • Excellent problem-solving abilities and a proven capacity to thrive in a collaborative team environment.
- • Effective communication skills, with the ability to clearly articulate complex technical concepts to both technical and non-technical audiences.
🏖️ Benefits
- • Competitive hourly compensation for the duration of the internship.
- • Dedicated mentorship and hands-on learning opportunities guided by experienced Machine Learning Engineers.
- • Structured intern programming, including workshops, networking events, and team-building activities.
- • A dynamic and collaborative work environment within a rapidly growing company at the forefront of the AI economy.
Skills & Technologies
Python
AWS
Azure
GCP
TensorFlow
Junior
Onsite
Degree Required
About Handshake Technologies, Inc.
Handshake Technologies provides a cloud-based career-services platform that connects university students, recent graduates, and employers. The software enables institutions to manage job postings, career fairs, on-campus interviews, and employer relations while giving students tools to discover internships and entry-level roles and giving employers access to early-career talent across a network of partner colleges and universities.
