Foundation Models ML Engineer - On-Device, Privacy-Focused

Apple Inc.; Seattle (WA); On-site; USD 184,700 - 324,800; Full time

Benefits offered by this job

Medical and dental coverage

Employee stock programs

Relocation assistance

Job summary

Apple Inc. is seeking a Machine Learning Engineer to design scalable ML infrastructure for foundation models across text, image, speech, and multi-modal domains. The role focuses on productionizing state-of-the-art AI algorithms with privacy and security in mind for on‑device intelligence.

The candidate will work on pre‑training and mid‑training strategies, optimize performance, and collaborate across teams to deliver production-ready AI solutions at scale.

Qualifications

• MS or PhD in Computer Science, Machine Learning, or related technical field.
• Expert-level programming skills in Python.
• Proficiency in ML frameworks such as Jax, PyTorch, TensorFlow.
• Strong background in distributed training, model optimization, and ML infrastructure.
• Experience with large-scale model training and deployment.
• Familiarity with Kubernetes, Docker, and cloud platforms (AWS, GCP, Azure).
• Distributed computing frameworks.

Responsibilities

• Design and implement scalable ML infrastructure for foundation models across text, image, speech, and multi-modal domains.
• Collaborate with teams to productionize state-of-the-art AI algorithms.
• Optimize models for performance, efficiency, and on-device intelligence.
• Implement ML systems with stringent privacy and security requirements.
• May manage a small team of engineers.

Skills

Python

Distributed training

Model optimization

ML infrastructure

Education

MS or PhD in Computer Science, Machine Learning, or related field

Tools

Jax

PyTorch

TensorFlow

Kubernetes

Docker

Cloud platforms (AWS, GCP, Azure)

Job description

Apple Inc. is seeking a Machine Learning Engineer to design scalable ML infrastructure for foundation models across text, image, speech, and multi-modal domains. The role focuses on productionizing state-of-the-art AI algorithms with privacy and security in mind for on‑device intelligence.

The candidate will work on pre‑training and mid‑training strategies, optimize performance, and collaborate across teams to deliver production-ready AI solutions at scale.