This role pays more than
60%
of similar roles. Most pay
$196,750–$254,750
— the shaded band above.
At the midpoint, this role pays about
$242k
versus about
$226k
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.
The Senior Machine Learning Engineer, Search & Knowledge Platforms joins the Answers, Knowledge & Information team to advance apple intelligence, assistant response ranking, and search technologies. This role involves building large language models at scale for Siri’s question and answering systems while developing core software infrastructure for natural language understanding. The engineer will design low-latency runtime tech stacks for global search, build data pipelines for large-scale processing, and evaluate and benchmark natural language processing models for deployment. Key technical requirements include proficiency in PyTorch, TensorFlow, and JAX to train and deploy deep learning models. Candidates should possess skills in search relevance ranking, query understanding, and summarization. The role addresses the challenge of improving how users access information across products like Spotlight and Safari by leveraging advanced LLM techniques for intent ranking and document retrieval.
What does a Machine Learning Engineer earn in Washington?
Median $241750 from 66 postings across 14 companies.
LLM
PyTorch
TensorFlow
JAX
RAG
Natural Language Processing
Information Retrieval
Distributed Systems
Inference Optimization
Machine Learning
Deep Learning
Machine Learning
NLP
Large Language Models
Python
C++
PyTorch
TensorFlow
Jax
BERT
T5
Information Retrieval
Recommender Systems
Data Engineering
Software Engineering
Machine Learning
Python
Go
Large Language Models (LLMs)
Natural Language Processing (NLP)
Information Retrieval
Retrieval-Augmented Generation (RAG)
Prompt Engineering
Data Science
A/B Testing
Statistical Hypothesis Testing
Data Pipelines
Distributed Inference
Model Quantization
Search Ranking