ML Researcher, Apple Foundation Models
Core
Building frontier foundation models optimized for Agentic, Reasoning, and Coding capabilities, specifically for Apple silicon and private, personal OS experiences.
Role type
Senior IC machine-learning researcher (agentic systems & RL)
Builds
Autonomous coding agents, agentic systems for multi-step workflows, and foundation models for reasoning and coding.
Domain
Artificial Intelligence / Machine Learning / Software Engineering
Deliverable
production ML models
Required skills
deep learning, reinforcement learning, Python, JAX/PyTorch/Tensorflow, mathematical reasoning, reward modeling, RL scaling laws, distillation, alignment, long-context handling
Preferred skills
RLHF, GRPO, PPO, RLVR, repository-level code understanding, tool-use planning, user simulation, sparse attention, context compression
Technologies
JAX, PyTorch, Tensorflow, SWE-Bench
Responsibilities
Train models via RL to reason from first principles; build autonomous coding agents operating in real repositories; develop agentic systems handling multi-step workflows with error recovery; solve problems involving RL with verifiable rewards for mathematical reasoning; scale RL compute allocation; align models across capability stages.
Seniority
Senior, hands-on IC
