Machine Learning Engineer

Handhake’s Growth Relevance team is hiring a Machine Learning Engineer I to build and improve ML systems that support lifecycle optimization, personalized notifications, and monetization.

Responsibilities

• Develop and iterate on machine learning models and features that impact user experience across lifecycle, notifications, and monetization, with guidance from senior engineers
• Collaborate with senior engineers, data scientists, and product managers to build and refine machine learning models for product improvements and user experience
• Build technical depth alongside experienced ML practitioners, focusing on best practices for model development, experimentation, and production deployment

Requirements

• 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; hands-on experience with scikit-learn, PyTorch, or TensorFlow
• Experience deploying and evaluating agentic workflows
• Strong foundation in core ML concepts: classification, regression, ranking, and model evaluation

Technologies

• Python
• scikit-learn
• PyTorch
• TensorFlow
• GCP
• AWS
• Azure

Extra Credit

• Master’s degree or currently pursuing an advanced degree in a relevant field
• Exposure to recommendations, personalization, NLP, deep learning, LLMs, or explainable AI
• Familiarity with the ML lifecycle, including experiment tracking, model monitoring, and feature pipelines
• Experience with cloud platforms (GCP, AWS, or Azure)
• Clear communicator able to translate technical work for diverse audiences
• Collaborative mindset with cross-functional work alongside product, analytics, and engineering teams

Compensation

• $150,000 - $189,000 per year
• Offers Equity

Benefits

• Offers Equity
• 401(k) match
• Competitive compensation
• Financial coaching
• Paid parental leave
• Fertility benefits
• Parental coaching
• Medical, dental, and vision
• Mental health support
• $500 wellness stipend
• $2,000 learning stipend
• Ongoing development
• Internet
• Commuting
• Free lunch and gym in the SF office

• Location: San Francisco, CA (onsite)
• Employment type: Full time
• Department: Engineering