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Staff Machine Learning Systems Engineer

Reddit· ML & Search
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Hybrid (United States)$230k - $322kFull-timePosted 7mo ago

About the role

Staff ML Infrastructure Engineer leading development of a platform for large scale ML models at Reddit, focusing on end-to-end MLOps, scalable graph ML codebase, and distributed training optimization.

Responsibilities

  • 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

Qualifications

  • 8+ 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
  • Hands-on experience administering and integrating MLOps tools for experiment tracking, model serving, and model registries (e.g. MLflow or Wandb)
  • Proficiency with Python, PyTorch, TensorFlow, etc.
  • Deep experience working with distributed training frameworks, including Ray and Kubernetes
  • Strong focus on scalability, reliability, performance, and ease of use; advocate for platform users
  • Strong organizational & communication skills
  • Experience with graph databases (Neo4j, JanusGraph, TigerGraph) is a plus
  • Experience with graph neural networks (GNNs) and graph ML frameworks (PyTorch Geometric, Deep Graph Library) is a plus

Skills

Required:ML infrastructureML optimization and profilingCloud-based ML platform technologiesMLOps tools (MLflow, Wandb)Programming languagesDistributed training frameworks
Nice to have:Graph databasesGraph neural networks

Benefits

  • medical, dental, and vision insurance
  • 401(k) with employer match
  • generous time off for vacation
  • parental leave
Last updated Oct 7, 2026. Interested? Apply on the company site.
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