This role pays more than
55%
of similar roles. Most pay
$192,050–$249,000
— the shaded band above.
At the midpoint, this role pays about
$216k
versus about
$221k
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
88 open roles
on FindRole.
Listed pay typically runs
$209,000–$313,000
across 78 roles with salary data.
Machine Learning Engineer, Level 4 will join the engineering team to build and deploy machine learning models that power core products for millions of users. The role involves owning the full machine learning lifecycle, from initial data analysis to production deployment, while collaborating with cross-functional teams to prototype and launch features. The candidate will solve large-scale, real-world problems involving ranking, recommendations, search, content understanding, and image generation. Required skills include a strong understanding of machine learning algorithms, experience with system design, and the ability to use AI tools to streamline development while ensuring architectural integrity. Preferred technical expertise includes proficiency with frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, or scikit-learn. The position focuses on developing scalable services that address complex technical challenges within the core product ecosystem.
What does a Machine Learning Engineer earn in Washington?
Median $241750 from 69 postings across 15 companies.
Build and deploy machine learning models that power core products for millions of users.
Apply modern ML techniques to solve large-scale, real-world problems.
Manage the full ML lifecycle from initial data analysis to production deployment.
Prototype and launch ML-driven features in collaboration with cross-functional teams.
Design and ship scalable services using high-velocity engineering workflows and AI tools.
Ensure all code meets rigorous standards for correctness, security, and production readiness.
Audit AI-generated outputs for architectural integrity, performance bottlenecks, and security risks.
What we're looking for
Bachelor's degree in a relevant technical field or equivalent practical experience.
3+ years of post-Bachelor’s machine learning experience, or a Master’s degree with 2+ years of experience, or a PhD in a relevant field.
Experience developing machine learning models for ranking, recommendations, search, content understanding, image generation, or other related applications.
Strong understanding of machine learning approaches and algorithms.
Proficiency in leveraging AI tools to streamline development while auditing output for architectural integrity and security.
Ability to solve open ambiguous problems and work effectively with internal and external partners.
Advanced degree in computer science or a related field (preferred).
Experience with frameworks like TensorFlow, PyTorch, Spark ML, scikit-learn, ranking infrastructures, and system design (preferred).
Machine Learning
TensorFlow
PyTorch
Spark ML
scikit-learn
Caffe2
System Design
Data Analysis
Model Training
Ranking
Recommendations
Search
Content Understanding
Image Generation
Production Deployment
Machine Learning
Large Language Models
LLM
Ranking Systems
Distributed Systems
TensorFlow
PyTorch
Caffe2
Spark ML
scikit-learn
Information Retrieval
System Design
Search Ranking
Indexing
Python
Java
Scala
C++
Spark
Flink
Ray
TensorFlow
PyTorch
Caffe2
scikit-learn
Distributed Systems
Big Data
Machine Learning
Vector Search
Inference Systems