Software Engineer, ML Infrastructure

Jobtailor; California (MO); On-site; USD 140,000 - 190,000; Full time

Job summary

Snapchat is seeking an experienced ML Infrastructure Engineer to design and optimize systems that support large-scale machine learning workloads. You will build feature generation and serving pipelines, develop efficient inference systems, and enable cloud-based training and evaluation.

Collaboration with ML engineers is essential to deploy models to production, while maintaining secure, production-grade code.

Qualifications

• Bachelor’s degree in a technical field or equivalent experience.
• 2+ years of post-Bachelor’s software development experience (or Master’s +1 year; or PhD).
• Experience building large-scale production ML systems or distributed/big data processing.
• Strong programming skills in Python, Java, Scala or C++.
• Understanding of distributed systems and ML infrastructure components.
• Experience with Spark, Flink, or Ray.

Responsibilities

• Design and optimize ML infrastructure for scale, reliability, and efficiency.
• Build and enhance feature pipelines powering online inference and offline data generation.
• Develop high-performance inference systems for fast model serving.
• Create scalable ML training, evaluation, and inference in the cloud.
• Build data management systems for scalable data collection, labeling, processing, and evaluation.
• Collaborate with ML engineers to deploy models to production.
• Use AI tooling and fast workflows to ship scalable, secure, production-grade code.

Skills

Python

Java

Scala

C++

Distributed systems

Big data processing

Education

Bachelor’s degree in Computer Science or equivalent

Master’s degree in a technical field

PhD in a relevant technical field

Tools

Spark

Flink

Ray

Job description

Responsibilities

• Design and optimize infrastructure systems for machine learning workloads at scale and drive reliability and efficiency improvements across Snapchat’s ML Infrastructure
• Build and enhance feature generation and serving pipelines that power online inferencing and offline training data generation
• Develop high-performance inference systems to ensure fast and efficient AI model serving
• Build infrastructure to perform scalable ML model training, evaluation, and inference in the cloud
• Build comprehensive data management systems for scalable data collection, labeling, processing, and evaluation
• Work closely with ML engineers to deploy cutting‑edge models into production
• Utilize AI tools and high-velocity engineering workflows to design and ship scalable services while upholding rigorous standards for code correctness, security, and production‑ready quality code

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
• Strong programming skills in Python, Java, Scala or C++
• 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