Software Engineer, ML Infrastructure, Core Inference, Level 4

About the role

Snap Inc. is a technology company that believes the camera presents the greatest opportunity to improve the way people live and communicate. The company operates Snapchat, a visual messaging app enhancing relationships with friends, family, and the world, along with Specs Inc., Bitmoji, Saturn, and other digital services. Snap Engineering builds fun, technically sophisticated products reaching hundreds of millions of Snapchatters daily.

This role is on the Core Inference team, part of the core ML Platform organization. The team builds and owns the machine learning infrastructure powering personalized experiences across Snap. As a centralized ML platform team, it enables teams across the company to deploy, optimize, and serve sophisticated ML models reliably and efficiently at scale. The team owns the end-to-end inference stack for recommendation models, embedding-generation models, and self-hosted large language models, supporting nearly every major organization at Snap including Ads, Content, Growth, Lenses, Security, and My AI.

Responsibilities

• Support the models powering personalized experiences across Discover, Stories, Spotlight, and other Snap products with ranking needs.
• Optimize, export, and prepare models for efficient production use while working across training and inference.
• Own the infrastructure used to host and serve 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 the inference components that power advertising models, while Ads teams generally own the ad products, formats, modeling objectives, and ranking strategies.
• Provide ranking and ML infrastructure for products such as Camera, Creative Tools, Maps, Chat, Memories, Games, and Minis when those products require model hosting or serving.

Requirements

• 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.

Preferred Qualifications

• Masters/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.

Skills

• Strong programming skills in Python, Java.
• 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.
• 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 to remain at the forefront of engineering trends and modern development practices.

Schedule

Snap practices a “default together” approach and expects team members to work in an office 4+ days per week.

Benefits

• Paid parental leave
• Comprehensive medical coverage
• Emotional and mental health support programs
• Compensation packages that let you share in Snap’s long-term success (equity in the form of RSUs)

Pay

In the United States, work locations are assigned a pay zone which determines the salary range for the position. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. The starting pay may be negotiable within the salary range for the position. These pay zones may be modified in the future.

• Zone A (CA, WA, NYC): Base salary range $157,000–$235,000 annually.
• Zone B: Base salary range $149,000–$223,000 annually.
• Zone C: Base salary range $133,000–$200,000 annually.

This position is eligible for equity in the form of RSUs.