Manager, Machine Learning Engineering

Apple Apple · Big Tech · Shanghai, China · Machine Learning and AI

Manager for a Machine Learning Engineering team focused on manufacturing applications at Apple. The role involves leading a team of ML and MLOps engineers to build, deploy, and scale AI-driven systems for the product lifecycle, from prototype to announcement. Requires technical expertise in AI, leadership skills, and experience with MLOps, Computer Vision, and scaling ML systems.

What you'd actually do

  1. Lead, mentor, and inspire a team of Machine Learning and MLOps Engineers to achieve technical excellence and professional growth.
  2. Collaborate with Project Managers, Data Engineers, and Manufacturing stakeholders to define requirements and prioritize high-impact AI use cases.
  3. Define the long-term vision and engineering roadmap, bridging the gap between data science and production operations.
  4. Foster a culture of collaboration, innovation, inclusivity, and accountability.
  5. Recruit, onboard, and retain top engineering talent with specialized skills in Deep Learning, Computer Vision, and MLOps.

Skills

Required

  • Software Engineering
  • Data Science
  • Machine Learning
  • leadership role
  • leading teams to deliver scalable, high-quality Machine Learning models into production environments
  • building and managing technical teams with a mix of algorithmic and infrastructure expertise
  • leading effective development processes to deliver high-quality production code
  • Deep Learning
  • Computer Vision
  • MLOps
  • Python
  • PyTorch/TensorFlow
  • SQL
  • Linux

Nice to have

  • MLOps frameworks (e.g., Kubeflow, MLflow)
  • containerization (Docker, Kubernetes)
  • scaling ML systems with large datasets
  • deploying models to Edge devices
  • mobile devices (CoreML)
  • cloud platforms (e.g., AWS)
  • DevOps practices
  • Agile/Scrum software development methodologies
  • Manufacturing
  • Industrial IoT
  • Smart Manufacturing environments

What the JD emphasized

  • Proven track record of leading teams to deliver scalable, high-quality Machine Learning models into production environments
  • Experience building and managing technical teams with a mix of algorithmic and infrastructure expertise
  • Experience scaling ML systems with large datasets

Other signals

  • leading teams to deliver scalable, high-quality Machine Learning models into production environments
  • building and managing technical teams with a mix of algorithmic and infrastructure expertise
  • scaling ML systems with large datasets