Sr. Machine Learning Research Engineer, Siri Speech

Apple Inc

Quick summary

Work type
On-site
Location
Cupertino, CA
Salary
$181,100–$318,400 / yr
Posted
20 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $223k
This role $250k
$165k most similar roles pay here $335k

This role pays more than 81% of similar roles. Most pay $195,875–$249,750 — the shaded band above. At the midpoint, this role pays about $250k versus about $223k for comparable roles.

Based on 239 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 638 open roles on FindRole.

Listed pay typically runs $171,600–$272,100 across 505 roles with salary data.

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At a glance

TL;DR · Sr. Machine Learning Research Engineer, Siri Speech

As a Senior Machine Learning Research Engineer on the Siri Speech team at Apple, you will collaborate with world-class engineers and scientists to develop innovative deep learning technologies that enhance natural language understanding, dialog generation, speech synthesis, recognition, and multi-modal interaction. Your daily work involves advancing efficient machine learning techniques for both server and device deployment, focusing on reducing latency, preserving privacy, and optimizing energy consumption while ensuring your research is published in top-tier conferences like NeurIPS or ICML. You will leverage expertise in model compression, algorithm optimization, and large-scale training to bring cutting-edge conversational AI solutions to millions of users, addressing complex challenges such as robust intent understanding and multi-turn dialog management.

What you'll do

  • Develop and deploy novel deep learning technologies to enhance Siri's capabilities.
  • Advance efficient machine learning techniques for speech and multi-modal modeling.
  • Focus on minimizing latency, preserving privacy, and saving energy in models.
  • Integrate advanced models into production to improve user experience daily.
  • Publish research findings in leading conferences while applying them practically.

What we're looking for

  • PhD in Mathematics, Computer Science, or related field, or equivalent industry experience.
  • Expertise in efficient deep learning with publications in top conferences like NeurIPS, ICML, ICLR.
  • Strong background in model compression and algorithm optimization techniques.
  • Experience in software design, coding, and parallel computing for large-scale systems.
  • Track record of applying machine learning to real-world products or services.

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