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AIML - Machine Learning Engineer, Siri Conversation Intelligence

Cupertino,California,United States

Machine Learning and AI

The Siri Conversation Intelligence (SCI) team is creating groundbreaking technology for large scale systems, spoken language, machine learning, and LLMs to enable better conversational experience with Siri. The features we create are redefining how hundreds of millions of people use their computers and mobile devices to fulfill their requirements and find what they are looking for. As part of the SCI team, you will work with the talent dense team who crafted the intelligent assistant that helps users get things done — just by asking. You will be responsible for doing research in the deep learning field and developing the most advanced natural language and conversation understanding systems. You should be passionate about working with software and platform engineers to integrate the models on-device and improve natural language understanding ability of Siri. Excellent interpersonal skills will be required to coordinate work across multiple teams to ship the state-of-the-art technology to production and impact all Siri users.

Description

As a member of this team, the successful candidate will: - Develop novel ML/DL models including LLMs for natural language and conversational understanding - Work with software and platform engineers to convert and compile the models to run on device and integrate them with runtime systems. - Optimize latency and performance of the models - Diagnose model errors and perform accuracy hill climbing for shipped products.

Minimum Qualifications

• Solid understanding of state-of-the-art technology in machine learning, deep learning (including LLMs) and natural language understanding.

• Excellent problem-solving (e.g. via building forward-looking prototype systems), critical thinking, strong communication, and collaboration skills

Key Qualifications

Preferred Qualifications

• 3-5+ years proven programming skills using standard ML tools such as C/C++, Python, PyTorch, Tensorflow, Hugging Face, etc.

• Hands-on experience working (training, fine-tuning, optimizing, deploying) with large models (e.g. LLMs).

• Hands-on experience applying common machine learning optimization techniques, like quantization and distillation, to reduce the resource consumption and/or eliminate latency

• Publication at top ML/DL/NLP conferences such as NeurIPS, ACL, EMNLP, etc. is a plus.

Education & Experience

Additional Requirements

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 $175,800 and $312,200, 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 (https://www.apple.com/careers/us/benefits.html) 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.

• Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.Learn more about your EEO rights as an applicant. (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf)

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