9 hours ago
Responsibilities
- Develop and optimize LLMs through domain-adaptive continual pretraining, post-training, preference optimization, and reinforcement learning.
- Build agentic systems supporting tool schemas, multi-turn reliability, reasoning, and verifier- or rubric-based learning loops.
- Optimize model deployment for latency, cost, reliability, and production integration.
- Develop synthetic-data generation, evaluation, and training pipelines for LLMs.
- Translate LLM research into shipped capabilities and user-facing Apple Services features.
- Lead cross-LOB initiatives from problem definition through execution and scaling while partnering with product, infrastructure, and foundation-model teams.
Requirements
- Bachelor’s or master’s degree in a quantitative field such as computer science, mathematics, statistics, or physics.
- Proficient programming skills in Python.
- Hands-on experience with deep learning toolkits such as Jax, TensorFlow, or PyTorch.
- Track record training or deploying large models or building large-scale distributed systems.
- Deep understanding of deep learning and large language models.
- Knowledge of natural language processing.
- PhD in a quantitative field is preferred.
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.