Snap
Software Engineer, ML Infrastructure, Level 5
$178K–$313K
Palo Alto, California +2 · Full-time · Posted Sep 25, 2026
- Location
- Palo Alto, California
Seattle, Washington
Los Angeles, California - Experience
- 6+ years post-Bachelor’s software development experience; or a Master’s degree plus 5+ years post-grad; or a PhD in a relevant technical field plus 2+ years post-grad.
- Education
- Bachelor’s degree in a technical field such as computer science or equivalent experience.
About the job
Build and optimize ML infrastructure for scalable model training, data management, feature serving, vector search, and production inference at Snap.
What you'll do
- Design and improve reliable, efficient infrastructure for large-scale ML workloads, including training and inference.
- Build data management systems and high-performance inference services; improve retrieval through vector search.
- Partner with ML engineers to deploy models and optimize storage and processing systems.
What they ask for
- Strong programming skills in Python, Java, Scala, or C++.
- Understanding of distributed systems and large-scale ML infrastructure; experience with big data frameworks such as Spark, Flink, or Ray.
- Track record operating highly available systems at significant scale.
- Experience building large-scale production machine learning systems, distributed systems, or big data processing.
Nice to have
- Experience with ML training platforms or AI inference optimization.
- Familiarity with TensorFlow, PyTorch, Caffe2, Spark ML, scikit-learn, or related frameworks.
Pay
$209,000-$313,000 annually (base salary); $199,000-$297,000 annually (base salary); $178,000-$266,000 annually (base salary)
Tools
Python, Java, Scala, C++, Spark, Flink, Ray, TensorFlow
AI focus
Develop and optimize machine-learning training and inference infrastructure, data and feature systems, and vector search for ranking and recommendation systems.
Model-written summary · the original posting is authoritative