AIML - Sr Machine Learning Engineer - Data and ML Innovation

Apple Inc

Actively hiring Posted today Verified listing
Seattle, WA Posted 1 day ago $139,500–$258,100 / year
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Salary context

Competitive pay

How this pay compares to similar roles

Similar $200k
This role $199k
$125k most similar roles pay here $272k

This role pays more than 51% of similar roles. Most pay $162,000–$238,655 — the shaded band above. At the midpoint, this role pays about $199k 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

As a Senior Machine Learning Engineer on Apple’s Data and Machine Learning Innovation team, you will play a pivotal role in advancing multi-modal models with strong agent and reasoning capabilities, focusing particularly on audio data. Your day-to-day responsibilities include innovating research in foundation models across the entire ML pipeline, from pre-training large-scale unlabeled audio corpora to fine-tuning task-specific datasets. You will design comprehensive data generation and curation frameworks, develop robust evaluation pipelines, and analyze multi-modal data to enhance model performance. Key technologies and tools include Python, PyTorch, TensorFlow, or JAX, with a focus on deep learning techniques such as self-supervised representation learning and active learning across modalities. This role demands expertise in areas like audio processing, natural language understanding, and statistical modeling, contributing to transformative products for billions of users globally.

Skills

Python PyTorch TensorFlow JAX AWS Kubernetes Docker CI/CD PostgreSQL MongoDB Git GitHub Slack Zoom Google Cloud Platform Azure Machine Learning Prometheus Grafana

What you'll do

  • Design and develop multi-modal data generation and curation frameworks for foundation models.
  • Create comprehensive model evaluation pipelines to support continuous improvement and performance assessment.
  • Analyze multi-modal data to understand its influence on model behavior and outcomes.
  • Develop self-supervised and semi-supervised representation learning pipelines for tasks like speech recognition.
  • Apply data selection techniques such as novelty detection and active learning across modalities to improve efficiency.

What we're looking for

  • 5+ years experience developing and evaluating machine learning applications.
  • Proficiency in Python with hands-on experience using deep learning toolkits like PyTorch or TensorFlow.
  • Deep technical skills in areas such as audio processing, natural language processing, or computer vision.
  • Ability to design and implement self-supervised and semi-supervised representation learning pipelines.
  • Experience in multi-modal data generation and curation framework development.

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