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Apple Inc.

AIML - Machine Learning Engineer , Apple Foundation Models

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What they do

A Machine Learning Engineer specializes in designing, building, and deploying machine learning models. They utilize statistical and mathematical techniques, parallelizing processing, hyperparameter tuning, and other optimization methodologies to improve model performance. Responsibilities also include collecting and preprocessing large datasets, conducting exploratory data analysis, working closely with data engineers to understand data requirements, and engineer input variables for machine learning models.

$126,465 / year median in North Carolina

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Job Description

AIML - Machine Learning Engineer ,
Apple Foundation Models Cary, North Carolina, United States Machine Learning and AI Summary Posted:
Sep 08, 2026
Weekly Hours:
40
Role Number:
200668999-1435 We are a tight-knit group of researchers and engineers responsible for building large scale frontier foundation models at Apple. We believe the most interesting breakthroughs in deep learning happen when we bridge the gap between raw model capability and user-centric utility.

In this role, you will play a critical role shaping the future of our LLM efforts, specifically in transforming our models into highly capable, intelligent assistants that power billions of Apple products. You will tackle core training challenges in instruction following, tool use, deep reasoning, and architectural adaption — designing models that deliver magical, deeply integrated, and privacy-forward experiences across the Apple ecosystem. You will work alongside a fast-growing team of world-class experts to explore novel training strategies, architectural adaptations, and advanced evaluation methodologies. Description
  • Design and iterate on end-to-end post-training strategies (including Reinforcement Learning) to unlock model capacities toward achieving specific model behaviors.
  • Pioneer novel algorithms for preference optimization, model steering, and safety.
  • Drive our data strategy by researching methods for high-quality human and synthetic data generation, automated data filtering, and curriculum learning to improve instruction following and reasoning.
  • Design robust evaluation methodologies to measure model helpfulness, factuality, and utility, moving beyond static benchmarks to accurately capture real-world performance.
  • Partner closely with pre-training teams to inform architecture choices, and with product teams to translate user requirements into model capabilities.
Minimum Qualifications Demonstrated expertise in deep learning with a focus on LLMs, post-training, or reinforcement learning, backed by a strong record of academic or real-world accomplishments in these or closely related domains. Proficient programming skills in Python and a major deep learning framework such as JAX or PyTorch. Masters/PhD, or equivalent practical experience, in Computer Science, Machine Learning, or a related technical field. Preferred Qualifications Experience training state-of-the-art large models at scale, with familiarity in distributed training challenges and trade-offs. Experience improving model performance on complex reasoning tasks (math, coding, logic). Experience with various transformers architectures and its transformations. Strong communication skills and a passion for working cross-functionally across Research and Product teams. 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. At Apple, we believe accessibility is a fundamental human right. You'll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong. Apple accepts applications to this posting on an ongoing basis.

Benefits

  • Dental Insurance