AIML ML Researcher

Apple Inc

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Work type: On-site
Location: Seattle, WA
Salary: $175,000–$308,500 / yr
Posted: 125 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Competitive pay

How this pay compares to similar roles

Similar $229k

This role $242k

$159k $325k

below market most similar roles pay here above market

This role pays more than 52% of similar roles. Most pay $204,200–$254,750 — the blue band above. At the midpoint, this role pays about $242k versus about $229k 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 3497 open roles on FindRole.

Listed pay typically runs $174,149–$277,600 across 2702 roles with salary data.

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At a glance

TL;DR · AIML ML Researcher

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AIML - ML Researcher, AFM joins a team building frontier foundation models for Apple silicon. This role involves working across the full training lifecycle, including pre-training and developing mid-training approaches to bridge general capabilities with task-specific performance. You will tackle frontier problems in reward modeling to resist reward hacking, handle sparse and delayed rewards in agentic settings, and align models for creative tasks and action-taking workflows. Key responsibilities include developing end-to-end voice interactions, natural language processing, and combining learning with knowledge. Required skills include deep learning expertise, a publication record in relevant conferences, and proficiency in Python with toolkits like JAX, PyTorch, or Tensorflow. Preferred experience includes coding large language models, speech recognition, reinforcement learning, and on-policy distillation.

Skills

Python PyTorch JAX TensorFlow Deep Learning Large Language Models Reinforcement Learning Natural Language Processing Speech Recognition Voice Models On-policy Distillation Foundation Models Reward Modeling Post-training Mid-training

What you'll do

Pre-train frontier foundation models and develop mid-training approaches to bridge general and task-specific capabilities.
Optimize foundation models specifically for Apple silicon hardware.
Develop reward modeling techniques to resist reward hacking and handle sparse or delayed rewards.
Align models for creative tasks and precise, action-taking workflows.
Build end-to-end voice interactions and natural language processing systems.
Combine deep learning techniques with external knowledge sources.
Implement reinforcement learning and on-policy distillation for large language models.
Execute post-training and mid-training techniques for large language 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 deep learning to products.
Proficient programming skills in Python and one deep learning toolkit such as JAX, PyTorch, or TensorFlow.
Ability to work in a collaborative environment.
Experience coding large language models (preferred).
Experience building end-to-end voice models (preferred).
Experience in speech recognition and generation (preferred).
Experience in reinforcement learning, on-policy distillation, and post-training or mid-training large language models (preferred).