Associate Machine Learning Engineer

• 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
• 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

### Benefits

• Health Insurance: Comprehensive medical , dental, and vision coverage
• Fertility and family forming: Through a partnership, Handshake offers comprehensive family benefits, including infertility treatments and a $15K stipend, to its employees.
• LGTBQ+ coverage: All medical plans cover transgender services.
• Mental health: Discounts on a variety of wellness apps and an Employee Assistance Program with access to five free counseling sessions.
• Tax savings: Tax-advantaged benefits to save money on healthcare, dependent care, and other expenses.
• Life & disability insurance: Essential benefits and automatic coverage with basic life insurance, plus short-term and long-term disability coverage.
• 401k match: Dollar-for-dollar match up to 1% of pay, with a max of $1,200 per year.
• Equity: Our equity program includes grants at hire, refresher grants after two years of tenure, and grants alongside promotions.
• Financial management: Handshake partners to provide free professional financial planning services.
• Learning & development: Employees are provided with an annual stipend to use towards professional development, career development workshops, manager trainings, and 1-on-1 coaching through external partnerships
• Community leader support: Employee Resource Group leaders are compensated with a quarterly bonus for the high-impact work the role requires
• Parental leave: Leaves of 16 weeks for birth-giving parents and 10 weeks for non-birth-giving parents; the policy applies to adoptions as well. Handshake also partners to provide one-on-one coaching on preparing for leave and coming back from leave
• Flexible time off: No accrued time off or waiting period to take vacation. Two paid flexible holiday days off to observe holidays that closely align with religious, cultural, and personal needs
• Sabbatical: Paid six-week sabbatical to recharge and reset beginning at six years of continuous, full-time employment, and every four years thereafter
• Volunteer time off: Two days off for social and civil activism, volunteer work, and/or any related activities, including attending and participating in protests- Bachelor’s degree in Computer Science, Data Science, or a related field
• Proficient in Python, with hands-on experience in frameworks such as scikit-learn, PyTorch, or TensorFlow
• 0–2 years of experience in machine learning, data science, or a related area
• Strong foundation in core ML concepts, including classification, regression, ranking, and model evaluation
• Exposure to areas such as recommendations, personalization, NLP, deep learning, LLMs, or explainable AI
• Master’s degree or currently pursuing an advanced degree in a relevant field
• Familiarity with the ML lifecycle (e.g., experiment tracking, model monitoring, feature pipelines)
• Experience with cloud platforms (GCP, AWS, or Azure)
• Collaborative mindset with experience working cross-functionally with product, analytics, and engineering teams
• Clear communicator, able to translate technical work for diverse audiences