Growth ML Engineer: Personalization & Lifecycle AI (Remote)

Apply; San Francisco (CA); On-site; USD 110,000 - 145,000; Full time

Benefits offered by this job

Equity

401(k) match

Parental leave

Medical/Dental/Vision

Wellness stipend

Learning stipend

Free lunch

Job summary

Handshake is hiring a Machine Learning Engineer I for the Growth Relevance team to build AI-powered solutions that guide students from education to meaningful career opportunities. You will work with embedding-based retrieval, Graph Neural Networks, and multi-stage rankers on a data platform with billions of data points, focusing on lifecycle optimization and responsible AI.

Collaborate with engineers, data scientists, and product managers to ship models and features that improve user engagement

Qualifications

• Bachelor’s degree in Computer Science, Data Science, or related field.
• 1–3 years of experience in machine learning or data science.
• Proficient in Python with hands-on experience in scikit-learn, PyTorch, or TensorFlow.
• Experience deploying and evaluating agentic workflows.
• Strong ML fundamentals: classification, regression, ranking, model evaluation.

Responsibilities

• Innovate ML models and features influencing user experience across lifecycle, notifications, and monetization.
• Collaborate with engineers, data scientists, and product managers to improve product features and user experience.
• Learn and apply best practices in model development, experimentation, and deployment.

Skills

Python

Machine Learning

Agentic workflows

Model evaluation

Education

Bachelor’s degree in Computer Science, Data Science, or related field

Tools

scikit-learn

PyTorch

TensorFlow

Job description

Handshake is hiring a Machine Learning Engineer I for the Growth Relevance team to build AI-powered solutions that guide students from education to meaningful career opportunities. You will work with embedding-based retrieval, Graph Neural Networks, and multi-stage rankers on a data platform with billions of data points, focusing on lifecycle optimization and responsible AI.

Collaborate with engineers, data scientists, and product managers to ship models and features that improve user engagement