ML Engineer, Apple Foundation Models

What you'll do

• Design data strategies, mixtures, and scalable systems for generating, curating, and assessing training data.
• Build synthetic-data, self-improvement, and data-flywheel methods for capabilities such as reasoning, planning, tool use, and multimodal understanding.
• Use benchmarks and model feedback to identify capability gaps and develop targeted data interventions, including reward modeling and alignment.

What they ask for

• Expertise in LLMs or multimodal LLMs, demonstrated through relevant publications or applying deep learning to products.
• Proficient in Python and at least one of JAX, PyTorch, or Tensorflow.
• Ability to work collaboratively.
• Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field, or equivalent practical experience.

Nice to have

• Experience with data-centric foundation-model solutions, large-scale data flywheels, or real-world feedback data under privacy and governance standards.
• Experience with agentic systems, model self-improvement, or multimodal foundation models.

Pay

USD $150,400 to $277,600 (base salary)

Tools

Python, JAX, PyTorch, Tensorflow

AI focus

Data-centric development and improvement of foundation models, including synthetic data, reasoning, agentic behavior, multimodal understanding, tool use, alignment, reward modeling, evaluation, and self-improvement.