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: 79 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Competitive pay

How this pay compares to similar roles

Similar $235k

This role $214k

$132k most similar roles pay here $325k

This role pays less than 63% of similar roles. Most pay $203,850–$265,512 — the shaded band above. At the midpoint, this role pays about $214k versus about $235k for comparable roles.

Based on 240 similar postings.

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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 1984 open roles on FindRole.

Listed pay typically runs $175,000–$277,600 across 1590 roles with salary data.

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At a glance

TL;DR · Machine Learning Researcher, Foundation Models

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AIML - Machine Learning Researcher, Foundation Models joins a team building frontier foundation models and developing mid-training approaches to bridge general capability with task-specific performance. This role involves working across the full training lifecycle, including pre-training, reward modeling to resist reward hacking, and handling sparse or delayed rewards in agentic settings. You will build data pipelines and evaluation suites for visual understanding and generation at scale while tackling challenges in vision-language modeling, image and video generation, and aligning models for creative tasks and action-taking workflows. The role requires proficiency in Python and deep learning toolkits like JAX, PyTorch, or TensorFlow. Candidates should possess expertise in deep learning, potentially with a publication record or experience applying techniques to products, specifically focusing on multimodal models, reinforcement learning, and on-policy distillation within the context of Apple silicon optimization.

Skills

Python PyTorch JAX TensorFlow Deep Learning Foundation Models Large Language Models Reinforcement Learning Vision-Language Modeling Video Generation Data Pipelines Reward Modeling On-policy Distillation Multimodal Models

What you'll do

Research and develop frontier foundation models across the full training lifecycle.
Develop mid-training approaches to bridge general capabilities with task-specific performance.
Optimize model architectures specifically for Apple silicon hardware.
Solve reward modeling problems to prevent reward hacking in agentic settings.
Align models for both creative tasks and precise, action-taking workflows.
Build large-scale data pipelines and evaluation suites for visual understanding and generation.
Develop and refine vision-language models, image generation, and video editing technologies.
Implement reinforcement learning and on-policy distillation techniques for multimodal models.

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 work effectively in a collaborative environment.
Experience training or adapting vision-language models.
Experience with image or video generation and editing.
Experience with post-training or mid-training large language models or multimodal models.
Experience with reinforcement learning and on-policy distillation.