AI Foundation Models Scientist: Multimodal Intelligence

AIToolboard; United States; On-site; USD 139,500 - 258,100; Full time

Benefits offered by this job

Apple employee stock programs

Discretionary RSU awards

Relocation assistance

Education expense reimbursement

Comprehensive medical and dental

Job summary

Apple Washington, US is seeking a highly skilled engineer to advance foundation models and agentic systems within the Multimodal Intelligence Team (MINT). You will tackle scaling, optimization, and integration challenges for models used across Apple products, aiming to deliver real-world AI experiences with privacy and efficiency.

You will stay current with research, develop data pipelines, and collaborate with engineers to deploy models from lab to production while aligning with Apple standards.

Qualifications

• BS and a minimum of 3 years relevant industry experience.
• Proficiency in Python and at least one modern deep learning framework (PyTorch, JAX, or TensorFlow).
• Experience with large-scale training pipelines and distributed systems.

Responsibilities

• Research, design, and optimize foundation models for real-world Apple products.
• Improve alignment, reasoning, and adaptation of large models for production deployment.
• Design and optimize large-scale data pipelines for robust training and evaluation.
• Collaborate with cross-functional teams to integrate models into software and devices.

Skills

Python

Deep learning

PyTorch

JAX

TensorFlow

Distributed systems

Education

BS in Computer Science or related field

PhD in Computer Science / ML (preferred)

Tools

PyTorch

JAX

TensorFlow

Job description

Apple Washington, US is seeking a highly skilled engineer to advance foundation models and agentic systems within the Multimodal Intelligence Team (MINT). You will tackle scaling, optimization, and integration challenges for models used across Apple products, aiming to deliver real-world AI experiences with privacy and efficiency.

You will stay current with research, develop data pipelines, and collaborate with engineers to deploy models from lab to production while aligning with Apple standards.