The future of AI is on-device. On the Siri team, we're solving the defining challenge: building and shipping powerful, LLMs that run with extreme efficiency across hundreds of millions of i Phones, Watches, and Macs. You will own the full ML stack, from data to deployment, bridging the gap between bleeding-edge research and product-critical models. This is where the hardest problems in applied ML are being solved.

Description:

The frontier of AI isn't in the cloud anymore. It's in your pocket. The real challenge is building models that are not only powerful but also private, efficient, and intelligent enough to act as a true assistant on a user's device.

At Apple's Siri team, this isn't a research paper-it's our daily work. We are building the next generation of LLMs and deploying them at the largest customer scale in the world. We're looking for engineers who thrive on solving the puzzles that exist at the bleeding edge of hardware, software, and machine learning.

This is a full-stack ML role for those who want to own their work from concept to silicon.

Your Playground:

• Training & Fine-Tuning: Architect and train LLMs specifically for assistant behavior. This is your opportunity to define what "reasoning" and "task completion" mean for a billion users.

• Performance & Optimization: Master the art of model surgery. You'll design and implement novel context and adapter strategies to make our models faster and smarter within the tight constraints of on-device deployment.

• Data as a Product: You understand that world-class models are built on world-class data. You will own the curation, augmentation, and evaluation pipelines that are the lifeblood of our systems.

• System Architecture: Your insights will shape not just the model, but the entire system. You'll work with cross-functional experts in software, research, and product to build a cohesive, intelligent experience.

We're a team that values velocity and pragmatism. We debate, we build, we measure, and we ship. If you're a builder with elite software engineering skills and a proven passion for pushing the boundaries of applied ML, your work will have a home here.

Ready to solve problems that will define the next decade of personal computing? Apply now.

• Preferred Qualifications

• Knowledge of Natural Language Processing

• Experience with Small Language Models

• Experience with Agentic AI

• Minimum Qualifications

• Experience with shipping LLM based products

• Excellent python engineering skills and knowledge of deep learning frameworks (one of Pytorch, Jax, Tensorflow)

• Machine Learning Research track record or Excellent knowledge of Machine Learning State of the Art

• Masters or PhD in Computer Science, Machine Learning Engineering or equivalent professional experience

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 .

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 $147,400 and $272,100, 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.