ML Infrastructure Engineer, Content Retrieval Platform

Socket.dev; Palo Alto (CA); On-site; USD 133,000 - 235,000; Full time

Benefits offered by this job

Paid parental leave

Comprehensive medical coverage

Mental health support

Job summary

Snap Inc. seeks a Software Engineer for the Content Retrieval Platform within the Content ML organization. You’ll design large-scale ML infrastructure, build pipelines for online inference and offline data generation, and deploy high-performance inference systems in the cloud.

You will work with ML engineers to push cutting-edge models to production, ensuring scalable, secure, and reliable services across a fast-moving team.

Qualifications

• 2+ years of post-Bachelor’s software development experience; or advanced degree with post-grad experience
• Experience building large-scale production ML systems and distributed systems
• Experience with big data processing and scalable ML infrastructure

Responsibilities

• Design and optimize infrastructure systems for ML workloads at scale
• Build and improve feature generation and serving pipelines for online inference
• Develop high-performance inference systems for AI model serving
• Create scalable ML training, evaluation and inference in the cloud
• Develop data management systems for data collection, labeling, processing, and evaluation
• Collaborate with ML engineers to deploy models into production
• Follow strict code correctness, security, and production-ready standards

Skills

Python

Java

Distributed systems

Big data frameworks

Collaboration

Production systems

Learning new concepts

AI/ML infra

Education

Bachelor's degree in Computer Science or equivalent

Master's degree preferred

Tools

Spark

Flink

Ray

TensorFlow

PyTorch

Caffe2

Spark ML

scikit-learn

Job description

Snap Inc. seeks a Software Engineer for the Content Retrieval Platform within the Content ML organization. You’ll design large-scale ML infrastructure, build pipelines for online inference and offline data generation, and deploy high-performance inference systems in the cloud.

You will work with ML engineers to push cutting-edge models to production, ensuring scalable, secure, and reliable services across a fast-moving team.