This role pays less than
51%
of similar roles. Most pay
$193,887–$254,750
— the shaded band above.
At the midpoint, this role pays about
$214k
versus about
$224k
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
3553 open roles
on FindRole.
Listed pay typically runs
$165,800–$277,600
across 2740 roles with salary data.
As an Applied Machine Learning Scientist, you will join a research and engineering team focused on developing advanced algorithms for sensing technologies across various mobile and wearable devices. You will design and implement machine learning models that transform raw image or time-series data into interpretable information to improve user experiences. Your daily work involves building scalable, automated processes for large-scale data analysis, model development, and validation using a massive computing platform of GPUs and CPUs. The role requires expertise in deep learning architectures like CNNs, RNNs, GANs, and active learning, alongside proficiency in Python and frameworks such as TensorFlow or PyTorch. You will also utilize signal processing, probabilistic modeling, and statistics to solve complex problems while collaborating with sensor architects and software engineers to build next-generation sensing technologies for consumer products.
Design and implement machine learning algorithms to process image or time-series data from various sensors.
Develop scalable, efficient, and automated processes for large-scale data analysis and model development.
Utilize massive computing platforms with thousands of GPUs and CPUs for model validation.
Create innovative tools and metrics to redefine how the team approaches technical problems.
Transform raw sensor data into interpretable information for use in consumer applications.
Collaborate with sensor architects and software engineers to build next-generation sensing technologies.
What we're looking for
BS degree in CS, EE, Statistics, or a related field and 3 years of experience.
Strong background in Deep Learning and classical Machine Learning, including CNN/RNN architectures, GAN, active learning, k-shot learning, and model complexity reduction.
Track record of new ML ideas proven by publications, patents, or open-source projects.
Experience with one or more Deep Learning packages such as TensorFlow or PyTorch.
Proficiency in Python programming.
MS or Ph.D. degree in CS, EE, Statistics, or a related field (preferred).
Experience in human computer interaction, signal processing, or high-performance implementations of deep learning algorithms (preferred).
Familiarity with C++, Objective-C, or large-scale data processing using Mesos, Spark, or Hadoop (preferred).
Python
C++
Generative AI
Reinforcement Learning
LLMs
PyTorch
TensorFlow
deep-learning
Agentic Systems
Distributed Training
Data Processing
Probabilistic Modeling
Statistics
Optimization Methods