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
24 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $219k
This role $250k
$164k most similar roles pay here $335k

This role pays more than 82% of similar roles. Most pay $192,525–$246,150 — the shaded band above. At the midpoint, this role pays about $250k versus about $219k 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 Engineer, ASR Infrastructure and Tools, Siri Speech

As a Senior Machine Learning Engineer on the Siri Speech team at Apple, you will join a cross-functional group of engineers and scientists dedicated to advancing speech recognition technology. Your day-to-day responsibilities include optimizing data pipelines using open-source tools like PySpark, Jax, and Ray, processing multi-modal datasets from diverse sources, and leveraging large-scale audio data to enhance model training. You will work closely with research and production teams to deliver cutting-edge voice experiences to millions of users globally. The role requires expertise in distributed data engineering frameworks such as Beam, Spark, Dask, and Ray, along with strong Python programming skills and experience handling complex, unstructured datasets. Ideal candidates have a background in speech understanding or generation and can thrive in a fast-paced environment where problem-solving and critical thinking are paramount.

What you'll do

  • Develop and optimize distributed data pipelines using PySpark, Jax, Ray.
  • Integrate multi-modal data from various sources into complex model training workflows.
  • Enhance speech recognition models by extracting signals from large datasets.
  • Collaborate with research teams to iterate on voice-based user experiences.
  • Apply distributed data engineering techniques in speech recognition and NLP.

What we're looking for

  • Experience processing large, complex, unstructured data sets.
  • Proficiency in distributed data processing frameworks like Beam, Spark, Dask, Ray.
  • Strong software engineering skills, preferably with Python.
  • Knowledge of open-source tools such as PySpark, Jax, and Ray.
  • Ability to optimize multi-modal data for model training pipelines.
  • M.S. or Ph.D. degree in Computer Science or a related technical field preferred.

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