ML Infrastructure Engineer — Scalable AI Platform

Snap Inc.; Santa Monica (CA); On-site; USD 157,000 - 235,000; Full time

Benefits offered by this job

Paid parental leave

Medical coverage

Mental health support

Equity compensation

Job summary

Snap Inc. is seeking a Software Engineer for the ML Platform Experience team to design and optimize ML infrastructure at scale. You will build feature pipelines, develop high-performance inference, and collaborate with ML engineers to deploy models into production.

The role emphasizes Python/Java, distributed systems, and big data frameworks, with a focus on scalable, secure, and production-ready code. In-office presence is preferred in Santa Monica, CA.

Qualifications

• Bachelor’s degree in computer science or equivalent experience.
• 2+ years of post-Bachelor’s software development experience; or Master’s +1 year; or PhD in a relevant field.
• Experience building large scale production machine learning systems and distributed systems.

Responsibilities

• Design and optimize infrastructure systems for ML workloads at scale.
• Build and enhance feature generation and serving pipelines for online inference and offline training data generation.
• Develop high-performance inference systems for fast model serving.
• Build infrastructure for scalable ML model training, evaluation, and inference in the cloud.
• Develop data management systems for scalable data collection and evaluation.
• Collaborate with ML engineers to deploy models into production.
• Use AI tools and fast development workflows while upholding code quality, security, and production readiness.

Skills

Python

Java

Distributed systems

Big data frameworks

Team collaboration

System performance

Learning agility

AI/ML knowledge

Education

Bachelor’s degree in computer science or equivalent

Master’s degree in a technical field

PhD in a relevant field

Tools

Spark

Flink

Ray

TensorFlow

PyTorch

Job description

Snap Inc. is seeking a Software Engineer for the ML Platform Experience team to design and optimize ML infrastructure at scale. You will build feature pipelines, develop high-performance inference, and collaborate with ML engineers to deploy models into production.

The role emphasizes Python/Java, distributed systems, and big data frameworks, with a focus on scalable, secure, and production-ready code. In-office presence is preferred in Santa Monica, CA.