Handshake is the career network for the AI economy. 20 million knowledge workers, 1,600 educational institutions, 1 million employers (including 100% of the Fortune 50), and every foundational AI lab trust Handshake to power career discovery, hiring, and upskilling, from freelance AI training gigs to first internships to full-time careers and beyond. This unique value is leading to unparalleled growth; in 2025, we tripled our ARR at scale.
Why join Handshake now:
Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel
Work hand-in-hand with world-class AI labs, Fortune 500 partners and the world’s top educational institutions
Join a team with leadership from Scale AI, Meta, xAI, Notion, Coinbase, and Palantir, among others
Build a massive, fast-growing business with billions in revenue
Handshake is hiring an Associate Machine Learning Engineer for the Growth Relevance team. AI is transforming how students navigate their careers, and we're committed to providing innovative, responsible AI-powered solutions that guide students from educational aspirations to meaningful career opportunities. In this role, you will contribute directly to this mission by developing, deploying, and enhancing machine learning systems focused on lifecycle optimization, personalized notifications, and monetization strategies.
You'll join a high-impact team leveraging cutting-edge ML infrastructure, including embedding-based retrieval, Graph Neural Networks, and multi-stage rankers built upon a robust data platform with billions of data points. Your work will drive critical marketplace metrics, enhance user engagement, and contribute to responsible AI practices around explainability, fairness, and quality.
What You'll Do
Innovator: Develop and iterate on machine learning models and features that directly influence user experience across lifecycle, notifications, and monetization — with guidance from senior engineers.
Collaborator: Partner with senior engineers, data scientists, and product managers to develop and iterate on machine learning models that improve product features and user experience.
Learner: Grow your technical depth by working alongside experienced ML practitioners, picking up best practices in model development, experimentation, and production deployment.
Bachelor’s degree in Computer Science, Data Science, or a related field
0–2 years of experience in machine learning, data science, or a related area
Proficient in Python, with hands-on experience in frameworks such as scikit-learn, PyTorch, or TensorFlow
Strong foundation in core ML concepts, including classification, regression, ranking, and model evaluation
Extra Credit
Master’s degree or currently pursuing an advanced degree in a relevant field
Exposure to areas such as recommendations, personalization, NLP, deep learning, LLMs, or explainable AI
Familiarity with the ML lifecycle (e.g., experiment tracking, model monitoring, feature pipelines)
Experience with cloud platforms (GCP, AWS, or Azure)
Clear communicator, able to translate technical work for diverse audiences
Collaborative mindset with experience working cross-functionally with product, analytics, and engineering teams
Handshake delivers benefits that help you feel supported—and thrive at work and in life.
The below benefits are for full-time US employees.
🎯 Ownership: Equity in a fast-growing company
💰 Financial Wellness: 401(k) match, competitive compensation, financial coaching
🍼 Family Support: Paid parental leave, fertility benefits, parental coaching
💝 Wellbeing: Medical, dental, and vision, mental health support, $500 wellness stipend
📚 Growth: $2,000 learning stipend, ongoing development
💻 Remote & Office: Internet, commuting, and free lunch/gym in our SF office
🏝 Time Off: Flexible PTO, 15 holidays + 2 flex days
🤝 Connection: Team outings & referral bonuses
Explore our mission, values, and comprehensive US benefits at joinhandshake.com/careers.
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Our mission at Handshake is to give all students the chance to build the career they want, no matter where they’re from or what school they attend.
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