Senior ML Systems & Program Lead

Socket.dev; Cupertino (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Apple Ads is seeking a senior ML-focused Engineering Program Manager to lead complex ML initiatives across our machine learning and algorithmic systems. You will partner with engineers, researchers, product managers, and leaders to drive roadmaps, manage dependencies, anticipate risks, and deliver scalable ML capabilities that support Apple Ads.

You will operate at the intersection of ML, engineering, and program execution, developing technical depth to understand end-to-end systems and how

Qualifications

• 5+ years leading complex technical programs related to AI/ML systems.
• Strong understanding of ML systems, software architecture, and dependencies across large-scale platforms.
• Track record of driving engineering roadmaps and execution across multiple teams and disciplines.
• Ability to engage credibly with engineers and technical leaders, ask effective questions, and identify risks beyond individual workstreams.
• Excellent written and verbal communication skills with technical teams and senior leadership.

Responsibilities

• Operate at the intersection of machine learning, engineering, and program execution.
• Develop enough technical depth to understand end-to-end systems and cross-team impacts.
• Influence teams toward shared outcomes and drive scalable ML capabilities for Apple Ads.

Skills

AI/ML program leadership

ML systems understanding

Roadmap & execution

Cross-functional collaboration

Communication with technical teams

Job description

Apple Ads is seeking a senior ML-focused Engineering Program Manager to lead complex ML initiatives across our machine learning and algorithmic systems. You will partner with engineers, researchers, product managers, and leaders to drive roadmaps, manage dependencies, anticipate risks, and deliver scalable ML capabilities that support Apple Ads.

You will operate at the intersection of ML, engineering, and program execution, developing technical depth to understand end-to-end systems and how