AIML Machine Learning Researcher

Apple Inc

Confirmed live yesterday Trusted

Quick summary

Work type: On-site
Location: Cupertino, CA
Salary: $184,700–$324,800 / yr
Posted: 79 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $234k

This role $255k

$168k most similar roles pay here $342k

This role pays more than 68% of similar roles. Most pay $202,800–$265,887 — the shaded band above. At the midpoint, this role pays about $255k versus about $234k 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 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 · AIML Machine Learning Researcher

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As an AIML - ML Researcher, AFM, you will join a fast-growing team of engineers and scientists focused on the full training lifecycle of frontier foundation models. You will work on pre-training, mid-training approaches for task-specific performance, and solving complex problems in reward modeling to resist reward hacking while handling sparse rewards in agentic settings. Your daily work involves developing end-to-end voice interactions, natural language processing, and combining learning with knowledge. The role requires proficiency in Python and deep learning toolkits like JAX, PyTorch, or TensorFlow. You will apply research to real-world use cases including speech recognition, generation, reinforcement learning, and on-policy distillation. This position addresses the technical challenge of aligning models for creative tasks and precise workflows while optimizing performance specifically for Apple silicon and integrated operating system experiences.

Skills

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

What you'll do

Develop and pre-train frontier foundation models for integrated OS experiences.
Implement mid-training approaches to bridge general capabilities with task-specific performance.
Optimize large language models specifically for Apple silicon hardware.
Solve reward modeling problems to prevent reward hacking in agentic settings.
Align models across creative tasks and precise, action-taking workflows.
Develop end-to-end voice interactions and speech recognition systems.
Apply reinforcement learning and on-policy distillation techniques to model training.
Integrate deep learning with knowledge bases for natural language processing.

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 major deep learning toolkit such as JAX, PyTorch, or TensorFlow.
Ability to work effectively in a collaborative environment.
Experience coding large language models.
Experience building end-to-end voice models, including speech recognition and generation.
Experience in reinforcement learning and on-policy distillation.
Experience in post-training and mid-training of large language models.