Software Engineer, ML Infrastructure, ML Data, Level 5

Snap Inc.•Los Angeles, CA

3d•$178,000 - $313,000•Onsite

About The Position

Snap Inc. is seeking a Software Engineer to join its ML Data Team. The team builds foundational data platforms, including robusta/hashi and mds, to support offline model training and online feature serving. It also provides tools for monitoring and assuring data quality, managing and registering features, tracing features through their lifecycles, and assisting with feature deprecation. The team focuses on storage and processing optimization to manage infrastructure costs while supporting the growth of Snap’s machine learning systems. The role involves designing and optimizing infrastructure for machine learning workloads at scale, improving reliability and efficiency, developing inference and model-training systems, building data-management capabilities, and working with ML engineers to deploy models into production. Snap follows a “default together” approach, expecting team members to work in an office 4 or more days per week.

Requirements

Strong programming skills in Python, Java, Scala, or C++.
Strong problem-solving skills focused on system performance, scalability, and efficiency.
Good understanding of distributed systems and infrastructure components for large-scale machine learning.
Experience with big data processing frameworks such as Spark, Flink, or Ray.
Ability to collaborate and work well with others.
Proven track record of operating highly available systems at significant scale.
Ability to proactively learn new concepts and apply them at work.
Bachelor’s degree in a technical field such as computer science, or equivalent experience.
At least 6 years of post-bachelor’s software development experience; or a master’s degree in a technical field and at least 5 years of post-graduate software development experience; or a PhD in a relevant technical field and at least 2 years of post-graduate software development experience.
Experience building large-scale production machine learning systems, distributed systems, or big data processing systems.

Nice To Haves

Master’s or PhD in a technical field such as computer science, or equivalent industry experience.
Experience working with ML training platforms or optimizing AI model inference.
Familiarity with ML frameworks such as TensorFlow, PyTorch, Caffe2, Spark ML, scikit-learn, or related frameworks.

Responsibilities

Design and optimize infrastructure systems for machine learning workloads at scale, improving reliability and efficiency across Snapchat’s ML Infrastructure.
Develop high-performance inference systems for fast and efficient AI model serving.
Build cloud infrastructure for scalable ML model training, evaluation, and inference.
Build data-management systems for scalable data collection, labeling, processing, and evaluation.
Work on vector search algorithms to improve the precision, recall, and scalability of retrieval systems.
Collaborate with ML engineers to deploy models into production.