Join the team redefining what a deeply personal and integrated assistant can be.
As part of the Siri organization, you will help shape one of the world's most widely used AI assistants, powered by our next-generation of Apple Intelligence, with capabilities like personal context understanding and on-screen awareness, built with privacy from the ground up. Your work will have direct, meaningful impact for users across iOS, iPadOS, macOS, watchOS, and visionOS.
This is a rare opportunity to build at the intersection of cutting-edge AI and human-centered design, shipping technology that is centered around users and their needs.
Description
We are seeking a candidate with a strong background in applied ML research and development, particularly in multimodal LLM, natural language processing/generation, speech generation/understanding, to join our cross-functional team focused on advancing capabilities in systems like Siri. We are looking for applied ML researchers who can develop end-to-end solutions from data scaling to necessary model implementation and training while collaborating with other engineering teams to bring research to production. You will develop and deploy novel deep learning technologies that make Siri more intelligent, natural, and useful. To succeed in this role, you should be a strong researcher and engineer, an excellent programmer, and a creative problem solver who enjoys learning new techniques, improving systems, and taking ownership of complex problems. You should also thrive as a team player in a fast-paced environment.","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
Preferred Qualifications
Experience in reinforcement learning
Experience with Speech LLMs or other Multimodal LLMs
Experience with building & deploying AI agents and LLMs
Experience with large scale machine learning training/evaluation
Data-centric vision and hands-on experience in developing and scaling foundation models
Minimum Qualifications
M.S. or 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
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $184,700 and $324,800, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
