This role pays more than
88%
of similar roles. Most pay
$205,425–$255,300
— the shaded band above.
At the midpoint, this role pays about
$286k
versus about
$230k
for comparable roles.
Based on 240 similar postings.
Employer
About Snap Inc.
Snap Inc. is a technology and camera company, best known for Snapchat, offering visual communication, augmented reality, and advertising products.
Snap Inc. currently has
76 open roles
on FindRole.
Listed pay typically runs
$209,000–$313,000
across 58 roles with salary data.
Staff Machine Learning Engineer, Search Ranking will join the engineering team to lead the development of next-generation search ranking systems. The role involves designing, building, and improving machine learning models that determine relevance, quality, personalization, and utility for search results at scale. Key responsibilities include owning major ranking initiatives from problem definition through experimentation, developing models using techniques like learning-to-rank, deep retrieval, neural ranking, sequence models, embeddings, multi-task learning, and large-scale feature engineering. The candidate will work with Python, C++, Java, or Scala while utilizing infrastructure tools such as Spark, Flink, Beam, TensorFlow, PyTorch, and JAX. This role focuses on solving complex problems in search ranking, including intent understanding, engagement optimization, and balancing multiple objectives like diversity, freshness, and safety within high-scale production environments involving advanced technologies like LLMs and retrieval-augmented systems.
What does a Machine Learning Engineer earn in Washington?
Median $241750 from 66 postings across 14 companies.
Machine Learning
Python
Go
LLMs
Prompt Engineering
Information Retrieval
Natural Language Processing
RAG
Data Pipelines
A/B Testing
Statistical Hypothesis Testing
Search Ranking
Model Quantization
Distributed Inference
Data Science
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
Machine Learning
NLP
Large Language Models
Python
C++
PyTorch
TensorFlow
Jax
BERT
T5
Information Retrieval
Recommender Systems
Data Engineering
Software Engineering