Manager, Machine Learning Engineer - Credit (Fintech)

Location: New York City office, hybrid; United States

Salary: $259,200–$395,280 annually, plus equity.

Company

hirify.global builds financial data connectivity tools and products used by developers, fintech applications, banks, and millions of consumers.

What you will do

• Lead, support, and develop Machine Learning Engineers and Data Scientists working on credit insights products.
• Set technical and product direction for LendScore, Income Insights, and the machine learning roadmap.
• Partner with Engineering, Product, and Data teams to prioritize opportunities and deliver reliable, scalable solutions.
• Guide machine learning models across experimentation, offline training, online serving, and monitoring.
• Support both 0-to-1 initiatives and the scaling and improvement of established products.
• Foster a high-ownership, bottom-up culture grounded in data-driven decisions and business impact.

Requirements

• 8+ years of experience training and serving AI or machine learning models in production environments.
• Experience leading a team of Data Scientists and Machine Learning Engineers.
• Experience in fintech lending and a strong understanding of how lending models are built and used.
• Experience building or working with data-intensive backend applications in large, distributed systems.
• Ability to code and iterate independently with Python, Spark, Jupyter notebooks, and standard machine learning libraries.
• Track record of taking ownership and driving projects to business impact.
• Ability to work effectively with technical and non-technical teams.
• Master’s degree or equivalent work experience in Computer Science, Mathematics, Engineering, or a closely related field.

Nice to have

• Experience in data analytics or data engineering.

Culture & Benefits

• Hybrid work from the New York City office.
• High-ownership, bottom-up, data-driven working environment.
• Medical, dental, and vision coverage.
• 401(k) and equity compensation.
• Commitment to diversity, equal opportunity, and reasonable accommodations during recruitment.