Senior Machine Learning Systems Engineer

Responsibilities

• As a Senior ML Infrastructure Engineer, you will lead development of a platform for large scale ML models at Reddit.
• Design end-to-end model lifecycle patterns (MLOps) to boost velocity of development for ML engineers, including data preparation, model management, experiment tracking, and more
• Zero-to-one development and support of a graph ML codebase and platform that abstracts away common patterns and enables greater model scalability and iteration
• Collaborate with ML engineers on performance tuning, including improving model training time, efficiency, and GPU training costs in a large, distributed ML training environment
• Optimize batch data processing within a data warehouse and with tools such as Apache Beam, Apache Spark, Ray Data, and more
• Architect pipelines to build and maintain massive graph data structures on the order of billions of nodes and tens of billions of edges
• Who You Might Be
• 5+ years of experience in ML infrastructure, including model training and model deployments
• Hands-on experience with ML optimization, including memory and GPU profiling
• Deep experience with cloud-based technologies for supporting an ML platform, including tools like GCP BigQuery, Google Cloud Storage, infrastructure-as-code (Terraform), and more

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