Machine Learning Engineer

ABOUT HANDSHAKE
Handshake was founded on a simple belief that everyone deserves a path to a great career, regardless of where they went to school or who they know. Today, we power 25 million job seekers, 1 million+ employers, and 1,600 educational institutions.
In 2025, we started Handshake AI and built the fastest-growing AI data business in history. We work directly with frontier AI lab researchers to create evaluations, publish benchmarks, and push the boundary of data. We’ve grown from 0to~1B run rate and pay ~$60M to over 30K individuals every month.
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
- Partner hand-in-hand with world-class AI labs, Fortune 500 partners and the world’s top educational institutions
- Work together with engineers, scientists, operators, and more from Palantir, Meta, Scale AI, and former YC founders
- Build a massive, fast-growing business with billions in revenue
About the Role
Handshake is hiring a Machine Learning Engineer I 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.
Desired Capabilities
- Bachelor’s degree in Computer Science, Data Science, or a related field
- 1-3 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
- Experience with deploying and evaluating agentic workflows
- 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
Perks
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

Employment type
FullTime

Work arrangement
No