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Sr. Machine Learning Engineer, Siri Speech

Apple

Sr. Machine Learning Engineer, Siri Speech

Apple

Cambridge, MA

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Annual team offsites

Flexible PTO policy

Health, dental, and vision coverage

Top Tier compensation with equity

Remote work flexibility

Learning and development stipend

Required Skills

PyTorch

SQL

Apache Spark

About the Role

The Speech Team within the Siri organization drives major speech recognition, synthesis and speech to speech model changes for various features deeply embedded throughout Apple's ecosystem. Our mission is to build cutting-edge infrastructure, datasets, and models that empower Siri conversational AI, Dictation and various speech enabled Apple Intelligence features with powerful capabilities across natural language understanding, dialog generation, speech recognition, and multi-modal interaction. We apply these technologies to create engaging, intelligent, and personalized conversational experiences for millions of Apple users.

We believe that the most impactful breakthroughs in deep learning emerge when we address real-world problems at scale. We develop speech to speech experiences and the underlying multimodal foundation model technology for current and future speech-enabled features across Apple's software, hardware, and services ecosystem. This allows for cutting edge applied research anchored in Apple specific production needs, while improving speech interaction experiences for Apple's customers around the world.

Responsibilities

You will work alongside a fast-growing team of world-class engineers and scientists to tackle core problems in dialog systems and foundation models- ranging from natural language understanding and multi-turn context tracking, to the integration of speech, text, and other modalities. You will develop and deploy novel deep learning technologies that make Siri more intelligent, natural, and useful. You'll help us advance the state of the art in natural language processing, speech and audio modeling, and multi-modal learning, with a strong focus on bringing your innovations into production. Your ideas will directly impact the daily lives of billions of users through Siri.

Minimum Qualifications

  • Demonstrated expertise in deep learning with publication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, KDD, ACL, ICASSP, Inter Speech) or a track record in applying deep learning techniques to products
  • Proficient programming skills in Python and one of the deep learning toolkits such as Py Torch, JAX, or Tensorflow

Preferred Qualifications

  • Experience with conversational AI or multimodal LLM
  • Experience with large scale machine learning training/evaluation
  • Data-centric vision about foundation model

Equal Opportunity

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.

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About Apple

Apple

Apple

Public

A technology company that designs, manufactures, and markets consumer electronics, personal computers, and software.

10,001+

Employees

Cupertino

Headquarters

$3.5T

Valuation

Reviews

4.0

10 reviews

Work Life Balance

4.0

Compensation

4.2

Culture

3.8

Career

3.5

Management

3.2

75%

Recommend to a Friend

Pros

Great coworkers and people

Excellent benefits and perks

Fast-paced and engaging work environment

Cons

High expectations and pressure

Management quality varies

Limited career progression opportunities

Salary Ranges

17,968 data points

Junior/L3

L2

L3

L4

L5

L6

M3

M4

M5

M6

Principal/L7

Senior/L5

Staff/L6

Junior/L3 · Data Scientist ICT2

0 reports

$121,979

total / year

Base

-

Stock

-

Bonus

-

$103,682

$140,276

Interview Experience

5 interviews

Difficulty

3.4

/ 5

Duration

28-42 weeks

Offer Rate

20%

Experience

Positive 20%

Neutral 40%

Negative 40%

Interview Process

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Behavioral Interview

5

Onsite/Virtual Interviews

6

Team Matching

7

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Culture Fit