This role pays more than
97%
of similar roles. Most pay
$189,912–$254,750
— the shaded band above.
At the midpoint, this role pays about
$345k
versus about
$222k
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.
Principal Software Engineer, Machine Learning Infrastructure will join the ML Inference team to oversee technical strategy and architecture for inference platform services. The role involves designing, implementing, and scaling critical engineering components to support machine learning deployment while ensuring high availability, scalability, and cost management. This individual will collaborate across teams to translate product requirements into technical solutions and provide leadership that influences company-wide initiatives. Key responsibilities include managing complex projects ranging from immediate feature launches to long-term research goals. The ideal candidate possesses expertise in large-scale distributed systems and high-throughput RPC services. Preferred technical skills include experience with Tensorflow, PyTorch, Kubernetes, GPU technologies, and LLM inference. The role focuses on solving the core engineering challenges of deploying and scaling machine learning models within a production environment to support innovative product features.
What does a Software Engineer earn in Washington?
Median $202800 from 326 postings across 28 companies.
Machine Learning
Large Language Models
LLM
Ranking Systems
Distributed Systems
TensorFlow
PyTorch
Caffe2
Spark ML
scikit-learn
Information Retrieval
System Design
Search Ranking
Indexing
Remote (Sunnyvale, CA)+5176 days ago
$296,300–$453,200
Python
PyTorch
TensorFlow
C++
Distributed Training
DDP
FSDP
GPU Computing
AWS
GCP
Azure
Data Processing Pipelines
Model Optimization
Profiling
Debugging