Engineering Program Manager - Apple Neural Engine/Machine Learning/Artificial Intelligence, Video Engineering

Summary

We are looking for an Engineering Program Manager to join the Video Engineering EPM team to work on cutting edge Apple Neural Engine (ANE), machine Learning and AI technology to deliver world-class Apple experience. The ideal candidate would have experience in product development and program/project/product management, proven leadership capabilities, excellent communication skills, and a desire to work with an amazing team to develop new technologies.

Minimum Qualifications

BS and a minimum of 10 years relevant industry experience in Electrical Engineering, Computer Science, or equivalent technical field Program management experience taking a product through all the stages of development. Experience with track record of hands-on software development Experience in embedded firmware/software development with relevant hardware, firmware, software consumer product development experience. Hands on experience about AI in the workplace beyond just using LLMs.

Preferred Qualifications

MS or PhD in Electrical Engineering, Computer Science, or equivalent technical field Understand and deals well with rapid changes, while remaining calm and flexible and in the face of uncertainty and/or ambiguity. Excellent communication, presentation, leadership and interpersonal skills with a cross functional collaborative mindset. Self-motivation with proven creative and critical thinking capabilities.

Description

Collaborate with multi-functional teams to drive, plan and track firmware and low-level software projects to support the technology development. Drive ML model inference, optimizations for performance, power and memory. Build development schedule, identify critical paths, and drive project/program thorough execution. Identify and highlight technical risk areas and mitigation strategies in partnership with Apple technologists. Ensure continuous tight coordination and communication with engineering teams. Synthesize and abstract large amounts of data into concise written and verbal analyses that provide key findings, recommendations and actionable items.