This role pays more than
78%
of similar roles. Most pay
$202,800–$254,750
— the shaded band above.
At the midpoint, this role pays about
$255k
versus about
$229k
for comparable roles.
Based on 240 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
1984 open roles
on FindRole.
Listed pay typically runs
$175,000–$277,600
across 1590 roles with salary data.
As a Sr. Machine Learning Research Engineer, Siri Speech, you will join the Siri organization to develop and deploy novel deep learning technologies that enhance the intelligence and natural feel of the assistant. You will work with a team of engineers and scientists to tackle core problems in efficient machine learning for dialog systems and foundation models, specifically focusing on natural language understanding, multi-turn context tracking, and the integration of speech, text, and other modalities. Your daily work involves advancing state-of-the-art research in speech and multi-modal modeling while optimizing models for server and device deployment to minimize latency and preserve privacy. You will utilize Python and deep learning toolkits such as JAX, PyTorch, or TensorFlow to solve complex problems involving model compression, algorithm optimization, and large-scale machine learning training and evaluation.
Develop and deploy novel deep learning technologies to improve Siri's intelligence and natural interaction.
Advance the state of the art in efficient machine learning for speech and multi-modal modeling.
Optimize advanced models to run efficiently on both server and mobile devices.
Minimize latency while preserving user privacy and reducing energy consumption during model execution.
Integrate speech, text, and other modalities into cohesive dialog systems.
Implement natural language understanding and multi-turn context tracking for AI assistants.
Translate research innovations into production-ready features for millions of users across multiple platforms.
What we're looking for
PhD in Mathematics, Computer Science, or another technical field, or equivalent industry experience.
Demonstrated expertise in efficient deep learning with a publication record in relevant conferences or a track record of applying these techniques to products.
Proficiency in Python and at least one deep learning toolkit such as JAX, PyTorch, or TensorFlow.
Strong expertise in efficient machine learning, model compression, and algorithm optimization techniques (preferred).
A track record in software design, coding, and parallel computing (preferred).
Experience with large scale machine learning training and evaluation (preferred).
Experience with on-device intelligence and learning with strong privacy protections (preferred).
Ability to work in a collaborative environment (preferred).
Deep Learning
Python
PyTorch
JAX
TensorFlow
Natural Language Processing
Speech Recognition
multi-modal learning
Conversational AI
Audio Modeling
Foundation Models
Machine Learning Training