20 hours ago
Responsibilities
- Develop novel algorithms and methodologies for LLM post-training and prompt optimization.
- Advance personalized intelligence by enabling models to understand user needs, adapt to personal context, and produce more relevant experiences.
- Research and prototype reinforcement learning, multimodal reasoning, context compaction, efficiency, and memory-system techniques.
- Partner with systems engineers to incorporate algorithmic innovations into scalable agentic experiences.
- Interface with large-scale modeling and data infrastructure.
Requirements
- PhD in electrical engineering, computer science, mathematics, physics, or computer engineering with a focus on computer vision and/or machine learning, or comparable professional experience.
- Strong machine learning and generative modeling fundamentals.
- Hands-on experience with pre-training or post-training of large language models and/or reinforcement learning.
- Familiarity with distributed training.
- Proficiency with machine learning toolkits such as PyTorch.
- Proven research contributions through publications in top-tier conferences or open-source algorithm contributions.
- Preferred: experience building and deploying multimodal LLMs.
- Preferred: experience building and deploying agentic systems and LLMs with tool use and memory capabilities.
Tech Stack
Categories
AI ResearchML Engineering
About Apple
Apple designs and sells consumer electronics, software, and services for consumers and professionals worldwide, including iPhone, Mac, iPad, Apple Watch, and AirPods, plus platforms like iOS/macOS and services such as the App Store, iCloud, Music, and TV+. Its business combines device sales with services and subscriptions and in-house silicon design. Founded in 1976, Apple is headquartered in Cupertino, California, and trades on NASDAQ as AAPL.