AIML - Machine Learning Engineer, Foundation Models

Apple Inc.
Cupertino, CA, United States
6 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Amazon Web Services Apple Products Microsoft Azure Cloud Computing Software Code Optimization Computer Programming Distributed Computing Environment Python (Programming Language) Machine Learning Open Source Technology Tensorflow
+9 more
Google Cloud Pytorch Large Language Models Deep Learning Kubernetes Information Technology Machine Learning Operations Artificial Intelligence Markup Language (AIML) Docker

Job description

We’re seeking skilled Machine Learning Engineers to transform cutting-edge research into scalable, production-ready AI solutions. We are looking for engineers who are passionate about building systems that push the frontier of deep learning in terms of scaling, efficiency, and flexibility and delight millions of users in Apple products. Description We build frontier foundation models that power intelligent experiences at Apple. Our team works across the full training lifecycle: including pre-training foundation models, and developing mid-training approaches that bridge general capability and task-specific performance. What makes our work distinct is that we’re engineering models specifically for Apple silicon and optimized for experiences that are private, personal, and deeply integrated into the OS. We’re solving frontier problems in reward modeling to resist reward hacking, handling sparse and delayed rewards in agentic settings, and aligning models reliably across the spectrum from open-ended creative tasks to precise, action-taking workflows.

Requirements

If you’re drawn to hard problems where the research and the product are inseparable, this is the team. Minimum Qualifications + MS or PhD in Computer Science, Machine Learning, or related technical field + Expert-level programming skills in Python + Proficiency in machine learning frameworks such as Jax, PyTorch, TensorFlow + Strong background in: Distributed training, Model optimization, and Machine learning infrastructure + Experience with large-scale model training and deployment + Familiarity with: Kubernetes, Docker, Cloud platforms (AWS, GCP, Azure) + Distributed computing frameworks Preferred Qualifications + Experience with foundation models and large language models + Background in multi-modal AI systems + Demonstrated ability to transform research prototypes into production systems + Published research or significant contributions to open-source ML projects + Understanding of on-device machine learning techniques 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.

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