Machine Learning Engineer, Siri Speech

Apple Inc.
Cupertino, CA, United States
4 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Starter
Experience required
1 year minimum
Compensation
$129,300.0
Working hours
Regular working hours

Tech stack

Artificial Intelligence Computer Programming Python (Programming Language) Machine Learning Tensorflow Reinforcement Learning Pytorch Large Language Models Siri Agentic-AI Build Management Information Technology

Job description

We are looking for a talented ML Research Engineer who is excited to work on SiriAI, which is used by millions of users across variety of Apple devices. Our Engineers are creative, inspired, innovative, energetic, self motivated people who love making and shipping products. Are you one of us? You will be responsible for improving multimodal algorithms that decide if a user is interacting with Siri or not. These algorithms include speaker recognition techniques. To succeed in this role, you must be a strong collaborator, and a creative problem solver who thrives in a fast-paced environment, working across teams and organizations.

Responsibilities

Develop and build multilingual, multimodal LLMs to improve speech and conversational experiences for Apple customers worldwide.

Advance the state of the art in multimodal 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

Requirements

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

Strong problem-solving skills and ability to work independently as well as in a team environment.

Excellent written and verbal communication skills.

Preferred Qualifications

M.S. in Electrical Engineering, Computer Science or related fields

1-2+ years experience in Machine Learning

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

Benefits & conditions

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 $129,300 and $225,300, 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.

About the company

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, tvOS, and visionOS.

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