ML Researcher, Apple Foundation Models

What you'll do

• Train models across pre-training, mid-training, and reinforcement learning, including for reasoning and coding tasks.
• Develop agentic systems for multi-step workflows, tool use, and long-horizon tasks.
• Research reward modeling, alignment, RL scaling, and context management for models optimized for Apple silicon.

What they ask for

• Deep learning expertise demonstrated by top ML or NLP conference publications, or a track record applying deep learning to products.
• Proficient programming in Python and one deep learning toolkit such as JAX, PyTorch, or Tensorflow.
• Ability to work collaboratively.
• PhD, or equivalent practical experience, in Computer Science or a related technical field.

Nice to have

• Experience with reinforcement learning for LLMs, including RLHF, GRPO, PPO, RLVR, reward modeling, or RL scaling laws.
• Experience with coding agents, agentic systems, distillation and alignment, or long-context efficiency.

Pay

USD 184,700–324,800 base salary

Tools

Python, JAX, PyTorch, Tensorflow, SWE-Bench

AI focus

Research and train foundation models using reinforcement learning for reasoning, coding agents, and multi-step agentic tasks; develop reward modeling, alignment, distillation, and long-context methods.