Machine Learning Research Engineer, Siri Comprehension & Planning, Siri Agent Modeling

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

Not verified last checked Jun 13, 2026

Salary

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401(k) match

Listed Source: EMPLR_CONTRIB_INCOME_AMT. source Last checked Jun 13, 2026.

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Market context

Median wage (BLS OEWS)

$111,944 national median

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

87% above the BLS national median for data and ml aggregate.

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Machine Learning Research Engineer, Siri Comprehension & Planning, Siri Agent Modeling Cupertino, United States of America 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 iPhones, 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. 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

Read the full description at jobs.apple.com. FewerJobs shows a source-linked preview and links to the original posting.