Staff Machine Learning Engineer (ml Platform - ML Development)

Apple Apple · Big Tech · New York, NY · Machine Learning and AI

Staff Machine Learning Engineer on the ML Platform team at Apple Ads, responsible for building and scaling shared ML platforms, frameworks, and services. The role focuses on enabling other teams to build and scale ML features, models, and applications, with a deep understanding of the ML lifecycle, deep learning architectures, and experience applying ML at scale in ads or recommender systems. Experience with privacy-preserving ML and AI/ML tooling is preferred.

What you'd actually do

  1. design, develop, and build world-class platform capabilities that will enable Apple Ads teams to improve and scale our ML features, models, and applications.
  2. design and develop secure and scalable back-end systems.
  3. building high-performing, elegant machine learning systems from the ground up, in close partnerships with various teams.
  4. define and refine architectures to meet the unique ad network challenges we must solve.
  5. building machine learning products which deliver on Apple's privacy commitments and change the way advertising works with data.

Skills

Required

  • Experience building shared ML platforms, frameworks or services used by multiple teams or organizations.
  • Deep understanding of the ML lifecycle, including training pipelines, evaluation methodologies, and deployment patterns.
  • Deep understanding of deep learning architectures (Transformers, LLMs, DNNs) and training frameworks (TensorFlow, PyTorch)
  • Prior experience applying ML at scale in Ads, recommender systems, or related domains.
  • Ability to communicate effectively, both written and verbal, with technical and non-technical multi-functional teams
  • Results oriented with strong technical leadership skills and a desire to work in a fast-paced collaborative work environment

Nice to have

  • Prior experience in privacy-preserving ML, distributed training at scale and techniques like model pruning, compression, quantization & distillation preferred.
  • Experience building AI/ML tooling and/or infrastructure at scale preferred
  • PhD/MS/BS in Computer Science or related field with 10+ years of industry experience in building large-scale distributed software systems

What the JD emphasized

  • Experience building shared ML platforms, frameworks or services used by multiple teams or organizations.
  • Deep understanding of the ML lifecycle, including training pipelines, evaluation methodologies, and deployment patterns.
  • Prior experience applying ML at scale in Ads, recommender systems, or related domains.
  • Experience building AI/ML tooling and/or infrastructure at scale preferred

Other signals

  • ML Platform
  • ML Systems
  • ML Features
  • ML Models
  • ML Applications