Job Details

Senior Machine Learning Engineer - Large Language Models (LLMs), Siri Planner Team

Cupertino, California, United States

Machine Learning and AI

Summary

Posted: Jun 04, 2025

Weekly Hours: 40

Role Number: 200607555

Join the Siri Planner team as an experienced Machine Learning Engineer and play a pivotal role in shaping the future of virtual assistants. You’ll contribute to revolutionizing how millions of Siri users worldwide interact with their Apple devices by building ground breaking AI solutions.

Description

As a Senior Machine Learning Engineer, you will lead initiatives to significantly advance Siri’s natural language understanding and planning capabilities using innovative LLM technologies.

YOUR CORE RESPONSIBILITIES WILL INCLUDE:

• Developing innovative systems for synthetic training data generation and implementing strategies for the continuous optimization of model performance.

• Designing and implementing agentic workflows and RAG systems to enhance Siri’s capabilities.

• Optimizing model performance for tool calling and reasoning tasks.

• Actively staying at the forefront of academic and industry research in LLMs, NLP, and agentic systems, and translating novel insights into practical solutions.

• Collaborating closely with a multidisciplinary team of researchers, software engineers, and product designers to seamlessly integrate AI innovations into the Siri user experience.

Minimum Qualifications

• Advanced degree (MSc/PhD) in Machine Learning, Computer Science, or a related quantitative field; or BSc with 5+ years of relevant industry experience.

• Proven hands-on experience in machine learning engineering for large-scale models, with a strong focus on generative AI, LLMs, Retrieval Augmented Generation (RAG), or agentic systems.

• Strong Python proficiency, including development, debugging, and design, coupled with extensive experience using ML frameworks (e.g. PyTorch, Jax, HuggingFace).

• Excellent problem-solving, critical thinking, and interpersonal skills, with a collaborative attitude.

Preferred Qualifications

• Applying LLMs for synthetic data generation (e.g. for knowledge distillation) or applying reinforcement learning for post-training or fine-tuning of LLMs.

• A successful track record of building and deploying end-to-end ML data pipelines (data preparation, storage, training, and inference) in cloud or on-premise environments.

• Experience with training, fine-tuning, and deploying LLMs in production environments.

• Proficiency in evaluating LLMs for specific product tasks and performance metrics.

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 about Apple Benefits. (https://www.apple.com/careers/us/benefits.html)

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 seek to promote 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) .

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote 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) .

Apple will not discriminate or retaliate against applicants who inquire about, disclose, or discuss their compensation.

Apple participates in the E-Verify program in certain locations as required by law.Learn more about the E-Verify program (https://www.apple.com/jobs/pdf/EverifyPosterEnglish.pdf) .

Apple is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. Reasonable Accommodation and Drug Free Workplace policy Learn more .

Apple is a drug-free workplace. Reasonable Accommodation and Drug Free Workplace policy Learn more .

Apple will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law. If you’re applying for a position in San Francisco, review the San Francisco Fair Chance Ordinance guidelines applicable in your area.

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.