This role pays less than
67%
of similar roles. Most pay
$194,850–$254,750
— the shaded band above.
At the midpoint, this role pays about
$203k
versus about
$225k
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.
AIML - Machine Learning Engineer - Computer Vision & Audio, MIND will join the Machine Intelligence, Neural Design team to drive the data and evaluation lifecycle for production models. The role focuses on designing and scaling high-performance data processing pipelines, performing in-depth failure analysis, and implementing advanced data augmentation techniques like GANs and synthetic data generation. You will build robust ETL/ELT pipelines using Spark and Airflow while ensuring data quality through automated validation and monitoring. Key responsibilities include crafting metrics to analyze user behavior and evaluating model performance across the stack. The position requires proficiency in Python, PyTorch, and handling unstructured audio and video signals for tasks like object detection and feature extraction. This role addresses the technical challenge of bridging hardware, software, and modeling to ensure ML systems are robust, efficient, and scalable.
What does a Machine Learning Engineer earn in Washington?
Median $241750 from 66 postings across 14 companies.
Design and maintain scalable ETL/ELT data pipelines using Spark and Airflow for large-scale datasets.
Implement advanced data augmentation techniques, including GANs and synthetic data generation, to address data scarcity.
Establish automated data validation checks and observability tools to monitor for drift and outliers.
Perform root-cause analysis on production model failures using advanced statistical methods.
Develop robust evaluation frameworks and metrics to monitor model performance and user behavior.
Process unstructured audio and video signals for object detection, feature extraction, and segmentation.
Optimize machine learning systems across the hardware and software stack for efficiency and scalability.
What we're looking for
Master's degree or equivalent experience in a technical or quantitative field.
Proficiency with Python and deep learning frameworks like PyTorch.
Proficiency working with unstructured data, specifically video and audio signals for object detection, pattern recognition, feature extraction, and segmentation.
Expertise in designing metrics and conducting metric change and performance analysis for model evaluation.
Experience with large scale training of machine learning models, including deep learning based models.
Experience with GPU-based distributed training and evaluation.
Background in Computer Vision, Audio, and Natural Language Processing.
Strong communication skills to present sophisticated technical concepts to both expert and non-expert audiences.
C++
Python
GPU Programming
Machine Learning
Swift
Numerical Computing
Distributed Training
Software Engineering
Low-level Programming
MLX
Apple Silicon