Machine Learning Researcher, Foundation Models

Apple Inc

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Cupertino, CA
Salary: $150,400–$277,600 / yr
Posted: 1 day ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $229k

This role $214k

$135k most similar roles pay here $293k

This role pays less than 61% of similar roles. Most pay $202,800–$254,750 — the shaded band above. At the midpoint, this role pays about $214k versus about $229k for comparable roles.

Based on 240 similar postings.

Employer

About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 2305 open roles on FindRole.

Listed pay typically runs $175,000–$280,000 across 1873 roles with salary data.

Most-posted roles

View all roles at Apple Inc

At a glance

TL;DR · Machine Learning Researcher, Foundation Models

Role Posting Log in to save

As a Machine Learning Researcher, Foundation Models, you will join a team focused on the full training lifecycle of frontier foundation models. You will work on pre-training, large language model architecture, and scientific scaling while addressing complex problems like reward modeling to resist reward hacking, handling sparse rewards in agentic settings, and aligning models for creative tasks and action-taking workflows. The role involves coding large language models and optimizing them specifically for Apple silicon. Required skills include proficiency in Python and deep learning toolkits such as JAX, PyTorch, or TensorFlow. Preferred expertise includes reinforcement learning, on-policy distillation, post-training, mid-training, and context lengthening. You will solve technical challenges where research and product are inseparable, focusing on the core problems of deep learning applied to real-world use cases within a collaborative environment.

Skills

Large Language Models Deep Learning Python PyTorch JAX TensorFlow Reinforcement Learning Pallas Triton Kernel Optimization Data Research LLM) architecture Mid-training On-policy Distillation

What you'll do

Research and develop frontier foundation models for integration into Apple products.
Conduct pre-training, architecture design, and scientific scaling of large language models.
Develop mid-training approaches to bridge general capabilities with task-specific performance.
Solve reward modeling problems to prevent reward hacking in agentic settings.
Align models across creative tasks and precise, action-taking workflows.
Optimize models specifically for Apple silicon hardware.
Implement reinforcement learning and on-policy distillation techniques.
Develop novel applications of deep learning for real-world user experiences.

What we're looking for

PhD or equivalent practical experience in Computer Science or a related technical field.
Demonstrated expertise in deep learning with a publication record in relevant conferences or a track record of applying techniques to products.
Proficiency in Python and at least one deep learning toolkit such as JAX, PyTorch, or TensorFlow.
Ability to code large language models.
Ability to work in a collaborative environment.
Experience in reinforcement learning and on-policy distillation (preferred).
Experience in post-training, mid-training large language models (preferred).
Experience in LLM context lengthening (preferred).