ML Engineer for Growth & Personalization

TrulyHired; San Francisco (CA); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Equity

401(k) match

Parental leave

Health coverage

Learning stipend

Remote + SF office

Job summary

Handshake is hiring a Machine Learning Engineer I for the Growth Relevance team in San Francisco, CA. You will develop and deploy ML models powering lifecycle, notifications, and monetization while collaborating with senior engineers and product teams.

You will work with embedding-based retrieval, Graph Neural Networks, and multi-stage rankers on a data platform with billions of data points, driving engagement and responsible AI practices.

Qualifications

• 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

Responsibilities

• 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.

Skills

Python

ML fundamentals

Model evaluation

Education

Bachelor's degree in CS/Data Science

Tools

scikit-learn

PyTorch

TensorFlow

Job description

Handshake is hiring a Machine Learning Engineer I for the Growth Relevance team in San Francisco, CA. You will develop and deploy ML models powering lifecycle, notifications, and monetization while collaborating with senior engineers and product teams.

You will work with embedding-based retrieval, Graph Neural Networks, and multi-stage rankers on a data platform with billions of data points, driving engagement and responsible AI practices.