4 days ago
Responsibilities
- Design and develop scalable model training and fine-tuning infrastructure for Apple Ads.
- Build shared ML platforms, frameworks, and services used by multiple teams or organizations.
- Develop capabilities for ML training, evaluation, deployment, inference, and agentic AI applications.
- Design distributed training systems and apply optimization techniques including model pruning, compression, quantization, and distillation.
- Define and refine architectures for high-performing, reliable, simple, scalable, and privacy-preserving ML systems.
- Partner with ML engineers, scientists, and technical and non-technical teams across and outside Apple Ads.
- Provide technical leadership and exercise judgment in selecting technologies and solutions for advertising-related ML challenges.
Requirements
- 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 including Transformers, LLMs, and DNNs, and training frameworks including TensorFlow and PyTorch.
- Experience applying ML at scale in advertising, recommender systems, information retrieval, or related domains.
- Experience with distributed training at scale and model optimization techniques.
- Experience building AI/ML tooling for model fine-tuning and training or infrastructure at scale.
- Strong written and verbal communication skills across technical and non-technical multifunctional teams.
- Strong technical leadership, ownership, curiosity, and ability to work in a fast-paced collaborative environment.
- Preferred experience with privacy-preserving ML techniques such as federated learning and differential privacy.
- Preferred experience with LLM training and inference, including pre-training, SFT, and verifiable RL rewards.
- Familiarity with Agentic AI.
- BS, MS, or PhD in Computer Science or a related field.
- 10+ years of industry experience building ML systems.
Tech Stack
PyTorchTensorFlow
Categories
About Apple
Apple designs and sells consumer electronics, software, and services for consumers and professionals worldwide, including iPhone, Mac, iPad, Apple Watch, and AirPods, plus platforms like iOS/macOS and services such as the App Store, iCloud, Music, and TV+. Its business combines device sales with services and subscriptions and in-house silicon design. Founded in 1976, Apple is headquartered in Cupertino, California, and trades on NASDAQ as AAPL.