below marketmost similar roles pay hereabove market
This role pays less than
72%
of similar roles. Most pay
$202,800–$254,750
— the blue band above.
At the midpoint, this role pays about
$203k
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
3497 open roles
on FindRole.
Listed pay typically runs
$174,149–$277,600
across 2702 roles with salary data.
As a Machine Learning Engineer, System Experience - Proactive, you will join the Agentic Search team to build the next generation of intelligent, on-device search experiences across Apple products. You will collaborate with machine learning, app engineering, and infrastructure teams to integrate personal search technologies into applications across iOS, macOS, and other platforms. Your daily responsibilities include designing durable, reusable software architectures, frameworks, and public-facing APIs for third-party developers. You will incorporate multi-system data streams into unified search experiences while upholding on-device privacy standards. The role requires proficiency in Swift, Objective-C, or equivalent high-level programming languages, along with experience in search systems, indexing, retrieval technologies, and machine learning principles. You must balance system trade-offs and runtime performance to optimize technologies for mobile constraints.
What does a Machine Learning Engineer earn in Washington?
Median $241750 from 69 postings across 15 companies.
Python
C++
PyTorch
JAX
TensorFlow
Retrieval-Augmented Generation
Large Language Models
Deep Learning
Natural Language Processing
Information Retrieval
Knowledge Distillation
Pruning
A/B Testing
Ranking Models
Embedding Models
Semantic Search
Multimodal AI
Python
C++
PyTorch
CUDA
GPU Kernel Optimization
Distributed Training
Data Pipelines
Inference Serving
Computer Architecture
Model Deployment
Data Ingestion
Profiling
Debugging
Claude