Senior Applied ML Researcher, Video Apps

Apple Inc

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$184,700–$324,800 / yr
Posted
34 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $229k
This role $255k
$159k most similar roles pay here $343k

This role pays more than 82% of similar roles. Most pay $204,200–$254,750 — the shaded band above. At the midpoint, this role pays about $255k 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 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 · Senior Applied ML Researcher, Video Apps

As a Senior Applied ML Researcher - Video Apps, you will join a team focused on designing, training, and deploying state-of-the-art models for visual and audio understanding. You will work at the intersection of computer vision, audio signal processing, and multimodal learning to build systems that can see, hear, and reason about the world. Your daily responsibilities include developing deep neural networks for video, image, audio, and audio-visual tasks, including temporal modeling, event detection, and cross-modal alignment. You will utilize Python and PyTorch to solve complex problems in speech, sound, and scene understanding. The role requires expertise in deep learning training workflows, linear algebra, probability, and optimization. You will translate problem statements into specific dataset requirements, neural network designs, and loss functions to improve creative workflows through generative AI and multimodal representation learning.

What you'll do

  • Design and train deep neural networks for video, image, audio, and audio-visual tasks.
  • Build models for audio-visual representation learning, cross-modal alignment, and fusion.
  • Develop solutions for video understanding, temporal modeling, and audio-visual event detection.
  • Implement systems for speech, sound, and scene understanding.
  • Perform multimodal classification, detection, and localization tasks.
  • Translate problem statements into specific dataset requirements, neural network designs, and loss functions.
  • Deploy state-of-the-art models to enhance creative workflows through generative AI.

What we're looking for

  • 4+ years of experience in deep learning or machine learning engineering.
  • 8+ years of hands-on experience with computer vision and/or audio modeling.
  • Expertise in deep neural networks and modern training workflows.
  • Proficiency in Python and deep learning frameworks, preferably PyTorch.
  • Solid understanding of linear algebra, probability, and optimization.
  • Ability to translate problem statements into dataset requirements, network designs, and loss functions.
  • PhD in computer science, machine learning, or a related field, or equivalent practical experience.
  • Experience with self-supervised/foundation model pre-training and publications in top-tier ML conferences.

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