Design and optimize infrastructure systems for machine learning workloads at scale and drive reliability and efficiency improvements across Snapchat’s ML Infrastructure
Build and enhance feature generation and serving pipelines that power online inferencing and offline training data generation
Develop high-performance inference systems to ensure fast and efficient AI model serving
Build infrastructure to perform scalable ML model training, evaluation, and inference in the cloud
Develop high-performance inference systems to ensure fast and efficient AI model serving
Build comprehensive data management systems for scalable data collection, labeling, processing, and evaluation
Work closely with ML engineers to deploy cutting-edge models into production
Utilize AI tools and high velocity engineering workflows to design and ship scalable services while upholding rigorous standards for code correctness, security, and production ready quality code

Bachelor’s degree in a technical field such as computer science or equivalent experience
2+ years of post-Bachelor’s software development experience; or Master’s degree in a technical field + 1+ year of post-grad software development experience; or PhD in a relevant technical field
Experience building large scale production machine learning systems, distributed systems or big data processing
Strong programming skills in Python, Java, Scala or C++
Strong problem-solving skills with a focus on system performance, scalability, and efficiency
Good understanding of distributed systems and the infrastructure components of large-scale ML
Experience with big data processing frameworks such as Spark, Flink, or Ray

Software Engineer, ML Infrastructure

Key skills