Senior Multimodal ML Researcher - Production-Scale LLMs

Apple Inc.; Seattle (WA); Hybrid; USD 205.000 - 309.000; Vollzeit

Benefits dieser Stelle

Stock programs

Education reimbursement

Medical & dental coverage

Employee stock purchase plan

Zusammenfassung

Apple Inc. seeks a senior technical leader to architect and deploy production-scale multimodal ML systems, spanning NLP and vision.

You will lead cross-functional teams across ML modeling, prototyping, validation and private learning, and partner with system engineers to integrate bleeding-edge algorithms for agentic experiences. The role requires strong ML fundamentals, published research or open-source contributions, and hands-on experience with training LLMs and adapting them for downstream

Qualifikationen

• PhD with 5+ years experience or MS with equivalent experience in CS/EE or related field, focus on ML.
• Hands on experience training or adapting LLMs for downstream tasks and alignment.
• Modeling experience at the intersection of NLP and Vision.

Aufgaben

• Architect and deploy production-scale multimodal ML systems.
• Lead cross-functional efforts across ML modeling, prototyping, validation and private learning.
• Collaborate with system engineers to prototype algorithmic innovations for agentic experiences.
• Interface with large-scale modeling and data infrastructure to enable scalable solutions.

Kenntnisse

Machine learning

LLMs training

NLP & Vision

Python programming

Research publications

Ausbildung

PhD/MS in CS/EE or related field

Tools

PyTorch

Distributed training

Large-scale data infrastructure

Jobbeschreibung

Apple Inc. seeks a senior technical leader to architect and deploy production-scale multimodal ML systems, spanning NLP and vision.

You will lead cross-functional teams across ML modeling, prototyping, validation and private learning, and partner with system engineers to integrate bleeding-edge algorithms for agentic experiences. The role requires strong ML fundamentals, published research or open-source contributions, and hands-on experience with training LLMs and adapting them for downstream