Sr. Machine Learning Engineer, ASR Infrastructure and Tools, Siri Speech

Apple Inc

Quick summary

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

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $224k
This role $250k
$154k most similar roles pay here $336k

This role pays more than 82% of similar roles. Most pay $198,800–$249,750 — the shaded band above. At the midpoint, this role pays about $250k versus about $224k 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 1723 open roles on FindRole.

Listed pay typically runs $162,500–$272,100 across 1398 roles with salary data.

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At a glance

TL;DR · Sr. Machine Learning Engineer, ASR Infrastructure and Tools, Siri Speech

As a Senior Machine Learning Engineer on the Siri Speech team, you will focus on advancing Apple’s speech recognition capabilities by leveraging cutting-edge distributed training technologies and large-scale data processing. Your daily tasks include optimizing multi-modal data ingestion into complex model training pipelines using open-source tools such as PySpark, Jax, and Ray, and extracting valuable signals from vast amounts of speech data to enhance modeling accuracy. Ideal candidates possess strong software engineering skills in Python, experience with distributed data processing frameworks like Beam, Spark, Dask, and Ray, and a background in handling large, complex datasets. Additional expertise in optimizing large-scale training jobs on high-performance computing clusters equipped with GPUs or TPUs is highly valued, as well as familiarity with speech understanding or generation technologies.

What you'll do

  • Develop and optimize distributed training pipelines for speech recognition models.
  • Integrate multi-modal data from various sources into complex model training workflows.
  • Utilize open-source tools like PySpark, Jax, and Ray to enhance data processing efficiency.
  • Extract valuable signals from large volumes of speech data to improve model accuracy.
  • Optimize the performance of machine learning jobs on high-performance computing clusters.

What we're looking for

  • Extensive experience processing large, complex, unstructured data.
  • Proficiency in distributed data processing frameworks like Beam, Spark, Dask, and Ray.
  • Strong software engineering skills with expertise in Python.
  • M.S. or Ph.D. degree in Computer Science or a related technical field preferred.
  • Experience optimizing and running large-scale training jobs on HPC clusters using GPUs/TPUs.

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