This role pays more than
60%
of similar roles. Most pay
$142,350–$222,050
— the shaded band above.
At the midpoint, this role pays about
$196k
versus about
$182k
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
55 open roles
on FindRole.
Listed pay typically runs
$209,000–$313,000
across 39 roles with salary data.
As a Software Engineer, ML Infrastructure at Level 4, you will join Snap Inc.’s dynamic team to scale and optimize the company’s machine learning infrastructure. Your responsibilities include designing high-performance systems for training and inference, enhancing feature generation pipelines, and developing comprehensive data management solutions. You’ll work closely with ML engineers to deploy advanced models into production while focusing on reliability and efficiency improvements across Snapchat’s ML Infrastructure. Ideal candidates possess strong programming skills in Python, Java, Scala, or C++, experience with big data processing frameworks like Spark or Flink, and a deep understanding of distributed systems and large-scale machine learning infrastructure. This role requires expertise in building scalable production ML systems and optimizing AI model inference to drive impactful innovations at Snapchat’s massive scale.
Skills
Python
Java
Scala
C++
Spark
Flink
Ray
TensorFlow
PyTorch
Distributed Systems
Big Data Processing
ML Frameworks
Scikit-learn
What you'll do
Design and optimize ML infrastructure systems for large-scale workloads.
Build feature generation pipelines for online inferencing and training data.
Develop high-performance inference systems for efficient AI model serving.
Create scalable cloud-based systems for ML model training, evaluation, and inference.
Construct comprehensive data management systems for scalable data handling.
Enhance reliability and efficiency across Snapchat’s ML Infrastructure.
Collaborate with ML engineers to deploy advanced models into production.
What we're looking for
Strong programming skills in Python, Java, Scala or C++
Experience building large-scale production machine learning and distributed systems
Expertise in optimizing ML infrastructure for reliability and efficiency
Proficiency with big data processing frameworks like Spark, Flink, or Ray
Ability to develop high-performance inference systems for AI models
Good understanding of distributed systems and ML infrastructure components
Familiarity with ML frameworks such as TensorFlow, PyTorch, or related tools