Jobs
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
PublicA 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
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