Senior Multimodal ML Engineer for Siri

Apple Inc.; Cupertino (CA); On-site; USD 185,000 - 325,000; Full time

Benefits offered by this job

Medical and dental coverage

Employee stock programs

Relocation assistance

Job summary

Apple Inc. in Cupertino, California invites applications for a Sr. Machine Learning Engineer, Siri Speech to advance multilingual, multimodal LLMs and speech understanding powering Siri across Apple platforms.

You will design end-to-end ML systems, train models, and deploy research into production, collaborating with research, engineering and design teams to deliver private, user-centric AI experiences at scale.

Qualifications

• MS/PhD in Electrical Engineering, Computer Science or related fields.
• 5-7+ years experience in Machine Learning.
• Experience in developing, training/tuning large generative models or LLMs.
• Experience with machine learning frameworks such as JAX and/or PyTorch.
• Proficient programming skills in Python.

Responsibilities

• Develop and build multilingual, multimodal LLMs to improve speech and conversational experiences for Apple customers worldwide.
• Advance the state of the art in natural language processing, speech and audio modeling.
• Design and build robust speech-centric LLM systems that enable next-generation conversational assistant features across Apple platforms.
• Collaborate closely with cross-functional partners in research, engineering, design, and production to deliver scalable, high-quality ML products.
• Stay current with emerging research and industry trends, and help define the future direction of AI-powered Siri experiences

Skills

LLMs

JAX

PyTorch

Python

Multimodal ML

Reinforcement learning

Speech LLMs

Education

MS/PhD in Electrical Engineering or Computer Science

Job description

Apple Inc. in Cupertino, California invites applications for a Sr. Machine Learning Engineer, Siri Speech to advance multilingual, multimodal LLMs and speech understanding powering Siri across Apple platforms.

You will design end-to-end ML systems, train models, and deploy research into production, collaborating with research, engineering and design teams to deliver private, user-centric AI experiences at scale.