Machine Learning Engineer

Handshake is a career platform committed to helping students navigate education and employment opportunities through responsible AI-powered solutions. The Machine Learning Engineer I will develop, deploy, and enhance machine learning systems for lifecycle optimization, personalized notifications, and monetization, while collaborating with senior engineers, data scientists, and product managers.

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

What they're looking for:

• 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
• 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

Benefits:

• Equity in a fast-growing company (for full-time US employees)
• 401(k) match (for full-time US employees)
• Financial coaching (for full-time US employees)
• Paid parental leave (for full-time US employees)
• Fertility benefits (for full-time US employees)
• Parental coaching (for full-time US employees)
• Medical, dental, and vision (for full-time US employees)
• Mental health support (for full-time US employees)
• $500 wellness stipend (for full-time US employees)
• $2,000 learning stipend (for full-time US employees)