ML Platform Director: Lead Scalable AI Infrastructure

PayJoy; San Francisco (CA); On-site; USD 300,000 - 321,000; Full time

Job summary

PayJoy is seeking an ML Platform Director in San Francisco to lead a team of ML and Software Engineers responsible for PayJoy's end-to-end ML ecosystem, including infrastructure, feature stores, model serving, and internal APIs. The role bridges Risk, Fraud, Product, and Engineering to ensure scalable, secure, and production-grade ML infrastructure.

You will guide the long-term vision for deployment, monitoring, and MLOps, while fostering innovation and maintaining stability.

Qualifications

• PhD or Master’s in Computer Science, Statistics, Engineering or a related field.
• 8+ years in Data Science or ML Engineering, with 4+ years in a leadership role.
• Proven track record designing and delivering large-scale ML systems.
• Deep understanding of the full ML lifecycle from feature extraction to production monitoring.
• Ability to translate business goals into scalable technical requirements and roadmaps.

Responsibilities

• Define the technical roadmap for the ML platform, modeling and internal APIs infrastructure.
• Mentor and manage a team of Staff and Senior ML Engineers; promote technical excellence.
• Act as liaison between Data Science/ML and Risk, Fraud, Engineering and Product.
• Own the long-term vision for ML infrastructure, including deployment, monitoring and MLOps.
• Guide the professional growth of direct reports and ensure challenging career trajectories.
• Champion adoption of new technologies and best practices to keep PayJoy at the forefront of financial ML.

Skills

Leadership

ML engineering

System design

Communication

ML lifecycle

Education

PhD or Master’s in CS/Statistics/Engineering

Job description

PayJoy is seeking an ML Platform Director in San Francisco to lead a team of ML and Software Engineers responsible for PayJoy's end-to-end ML ecosystem, including infrastructure, feature stores, model serving, and internal APIs. The role bridges Risk, Fraud, Product, and Engineering to ensure scalable, secure, and production-grade ML infrastructure.

You will guide the long-term vision for deployment, monitoring, and MLOps, while fostering innovation and maintaining stability.