Staff Applied AI and Machine Learning Engineer (Payments & Risk)

TL;DR

Staff Applied AI And Machine Learning Engineer (Fintech): Build and deploy machine learning models and AI-driven risk platforms in payments and risk domains with an accent on credit and fraud risk modeling, LLM integration, and scalable AI frameworks. Focus on designing, deploying, and maintaining high-security, reliable AI systems that safeguard user activities and money.

Location: Hybrid with offices in Denver, San Francisco, New York, Los Angeles, Seattle, and Toronto; employees in these locations expected to work onsite 2-3 days per week. Remote work allowed with secure, reliable internet connection.

Salary: $187,000 - $285,000 USD depending on location and experience; CAD salary for Toronto.

Company

hirify.global supports small businesses with payroll, health insurance, 401(k)s, and HR services, serving over 400,000 customers across the US and Canada.

What you will do

• Build and deploy machine learning models to identify, assess, and mitigate payment and risk-related threats.
• Drive research and development of AI models, including LLM integration, collaborating cross-functionally with engineering, product, design, and compliance teams.
• Develop scalable frameworks and libraries to enhance data analysis and modeling capabilities.
• Identify new data-driven opportunities to improve products and risk management solutions.
• Communicate findings and model results effectively to non-technical stakeholders.

Requirements

• Must have 8+ years experience in machine learning and AI, including credit or fraud risk modeling.
• Strong programming skills in Python, R, or similar statistical languages.
• Experience with predictive modeling, anomaly detection, ensemble methods, and optionally NLP and LLMs.
• Excellent communication skills to present complex findings clearly.
• PhD or Masters in quantitative field is a plus.
• Experience in Fintech industry is a plus.

Culture & Benefits

• Hybrid work model with flexible office attendance.
• Supportive and diverse workplace valuing inclusion and equal opportunity.
• Focus on employee well-being and accommodations.