AIML - Sr Machine Learning Engineer - Data and ML Innovation

Apple Inc

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$147,400–$272,100 / yr
Posted
1 day ago

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $200k
This role $210k
$132k most similar roles pay here $287k

This role pays more than 55% of similar roles. Most pay $162,000–$238,655 — the shaded band above. At the midpoint, this role pays about $210k versus about $200k 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 324 open roles on FindRole.

Listed pay typically runs $171,600–$272,100 across 230 roles with salary data.

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At a glance

TL;DR · AIML - Sr Machine Learning Engineer - Data and ML Innovation

As a Senior Machine Learning Engineer on Apple’s Data and Machine Learning Innovation team, you will play a pivotal role in advancing groundbreaking technology for multi-modal models with strong agent and reasoning capabilities. Your day-to-day responsibilities include innovating research in foundation models, particularly focusing on audio data, by working across the entire ML pipeline from pre-training to fine-tuning. You will design and develop comprehensive frameworks for generating and curating multi-modal data, build robust evaluation pipelines, and analyze data to understand its impact on model behavior. Additionally, you will contribute to academic publications and presentations, applying techniques like self-supervised learning and active learning to improve efficiency and reduce distributional gaps in various applications such as speech recognition and speaker identification. The role requires expertise in Python, deep learning toolkits like PyTorch or TensorFlow, and a strong background in areas like audio processing and natural language understanding.

What you'll do

  • Design and develop multi-modal data generation and curation frameworks for foundation models.
  • Develop comprehensive model evaluation pipelines to support continuous improvement and performance assessment.
  • Analyze multi-modal data to understand its influence on model behavior and outcomes.
  • Apply data selection techniques like novelty detection and active learning across modalities to improve efficiency.
  • Model data distributions using ML/statistical methods to uncover patterns and handle out-of-distribution challenges.
  • Design self-supervised and semi-supervised representation learning pipelines for tasks such as speech recognition.

What we're looking for

  • 5+ years experience developing and evaluating machine learning applications.
  • Proficiency in Python with hands-on experience using PyTorch, TensorFlow, or JAX.
  • Deep technical skills in areas like audio processing, deep learning, NLP, computer vision.
  • Ability to design, experiment, implement, and communicate ML solutions effectively.
  • Strong understanding of multi-modal foundation models preferred.
  • Publication record in top-tier machine learning conferences beneficial.

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