Software Engineer, ML Infrastructure, Core Inference, Level 4

Snap•Palo Alto, CA

5d•Onsite

About The Position

Snap Inc. is seeking a Software Engineer to join the Core Inference team within its core ML Platform organization. The team builds and owns machine-learning infrastructure that powers personalized experiences across Snap, enabling teams throughout the company to deploy, optimize, and serve sophisticated models reliably and efficiently at scale. It owns the end-to-end inference stack for recommendation models, embedding-generation models, and self-hosted large language models, supporting organizations including Ads, Content, Growth, Lenses, Security, and My AI. The role supports models for personalized experiences across Discover, Stories, Spotlight, and other products with ranking needs. It involves preparing and optimizing models for production, owning model-hosting and serving infrastructure, and working on LLM fine-tuning, reinforcement-learning infrastructure, serving, and inference optimization. The team also provides inference components for advertising models and ranking and ML infrastructure for other product areas when model hosting or serving is needed. Snap follows a “default together” approach, with team members expected to work in an office 4+ days per week. Snap offers paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages that include equity in the form of RSUs. U.S. annual base salary ranges vary by pay zone: Zone A (CA, WA, NYC) $157,000–$235,000; Zone B $149,000–$223,000; Zone C $133,000–$200,000.

Requirements

Strong programming skills in Python and Java.
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.
Adaptability in learning and applying evolving AI systems and tools and modern development practices.
Bachelor’s degree in a technical field such as computer science, or equivalent experience.
At least 2 years of post-Bachelor’s software development experience; or a technical Master’s degree and at least 1 year of post-graduate software development experience; or a PhD in a relevant technical field.
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

Support models powering personalized experiences across Discover, Stories, Spotlight, and other Snap products with ranking needs.
Optimize, export, and prepare models for efficient production use across training and inference.
Own infrastructure for hosting and serving recommendation models, embedding-generation models, and self-hosted LLMs.
Work on LLM fine-tuning, reinforcement-learning infrastructure, serving, and inference optimization.
Provide model-hosting and serving capabilities to teams across Ads, Content, Growth, Lenses, Security, My AI, and other product areas.
Own inference components that power advertising models.
Provide ranking and ML infrastructure for products such as Camera, Creative Tools, Maps, Chat, Memories, Games, and Minis when model hosting or serving is required.