ML Platform Director: Scale Secure AI Infra

Socket.dev; San Francisco (CA); On-site; USD 300,000 - 420,000; Full time

Job summary

PayJoy, a Public Benefit Corporation, is seeking an ML Platform Director in San Francisco to lead a team of ML and Software Engineers responsible for the end-to-end ML ecosystem, including ML infrastructure, feature stores, model serving, and internal APIs. You will bridge business strategy with technical execution, ensuring scalable, secure, world-class platforms.

You will mentor senior engineers, drive long-term ML infrastructure strategy, and champion production-grade reliability.

Qualifications

• PhD or master's in Computer Science, Statistics, Engineering or related field.
• 8+ years in Data Science or ML Engineering, with 4+ years in a leadership role.
• Proven track record delivering large-scale ML systems.
• Ability to translate complex business goals into actionable technical requirements.
• Excellent communication with executive leadership and stakeholders.

Responsibilities

• Define the technical roadmap for the ML platform, modeling and internal APIs infrastructure, overseeing long-term sustainability of data products and ML model + offers serving.
• Mentor and manage Staff and Senior ML Engineers; foster a culture of technical excellence.
• Act as liaison between Data Science/ML and business stakeholders (Risk, Fraud, Product).
• Own the long-term vision for ML infrastructure, including deployment, monitoring and MLOps; ensure performance and maintainability with safety standards.
• Guide the professional growth of direct reports with clear career trajectories.
• Champion adoption of new technologies (e.g., LLMs, graph databases) while maintaining production stability.

Skills

Leadership

ML Engineering

System design

Data Science

Stakeholder comms

MLOps

LLMs

Graph databases

Education

PhD or Master's in CS/Stats/Engineering

Tools

LLMs

Graph databases

Job description

PayJoy, a Public Benefit Corporation, is seeking an ML Platform Director in San Francisco to lead a team of ML and Software Engineers responsible for the end-to-end ML ecosystem, including ML infrastructure, feature stores, model serving, and internal APIs. You will bridge business strategy with technical execution, ensuring scalable, secure, world-class platforms.

You will mentor senior engineers, drive long-term ML infrastructure strategy, and champion production-grade reliability.