Machine Learning Engineer Manager Full-time

Summary
People here at Apple don’t just build products; we craft the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspire the innovation that runs through everything we do, from extraordinary technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it.

As a Machine Learning Manager, you will manage a team of dedicated engineers and data scientists to build innovative solutions that improve intelligent user experiences. Do you have a passion for solving complex problems and encouraging your team to think beyond the obvious? We are looking for an experienced manager with overseas experience and a deep understanding of machine learning, natural language processing, and reinforcement learning to join us. As a key leader, you will lead all aspects of the development of impactful ML solutions, that empower data-driven decision-making and transform our business processes.

Description
We are seeking an expert manager and technical lead in building technologies for sales.

Lead and encourage and develop innovative ML solutions that align with Apple’s vision and business goals.

Collaborate with team members, including business partners, data engineers, and platform architects, to find opportunities and translate requirements into scalable technical solutions.

Design and supervise the implementation of real-time and batch decision-making systems powered by innovative machine learning approaches.

Develop a culture of innovation and continuous learning, encouraging the team to stay at the forefront of advancements in machine learning, data engineering, and data visualization.

Ensure the operational health of deployed systems by supervising and responding to adversarial trends with agile decision-making.

Represent the team’s technical work in executive-level discussions and chip in for analytics and optimizations initiatives.

Education & Experience
Ph.D. in Computer Science, Machine Learning, Statistics, Operations Research, or a related field; or
Ph.D. in Math, Engineering, Economics, or hard science with significant data science or ML specialization; or
M.S. in a related field with proven experience leading teams in applying deep learning to real-world business problems.