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Staff Machine Learning Engineer (Ads ML Efficiency)

Reddit

Skills

Required

  • Python
  • Go / C++ / Rust / Java
  • debugging
  • performance engineering
  • systems optimization
  • software engineering
  • GPU architectures
  • performance analysis tools
  • cloud infrastructure
  • ML workloads

Preferred

  • ML
  • machine learning infrastructure / training systems / model serving platforms
  • distributed training frameworks
  • PyTorch
  • Ray
  • Tensorflow
  • Spark
  • identify bottlenecks

Join Reddit as a Staff Machine Learning Engineer in the ML Efficiency team. You will design and build systems to improve the efficiency of ML training and inference workloads, develop tooling for ML engineers, and optimize resource utilization. You will partner with ML researchers and product teams to identify bottlenecks and drive performance improvements. Your success will be measured by increased developer productivity, reduced infrastructure costs, and improved model quality.

Design and build systems that improve the efficiency of ML training and inference workloads, and develop tooling that helps ML engineers debug, profile, optimize, and monitor model performance.

Contributions to internal platforms used by multiple ML teams

About Reddit

Experience with building real time ML inference applications

Responsibilities

  • Partner with ML researchers and product teams to identify bottlenecks and drive performance improvements, and lead cross-functional initiatives that improve the productivity of Reddit ML engineers.
  • Drive technical strategy for ML platform scalability, reliability, and cost efficiency, and build benchmarking frameworks and performance dashboards for training and serving systems.

Requirements

  • Strong proficiency in Python
  • Profiency in at least one systems language (Go, C++, Rust, or Java) preferred
  • Experience building distributed systems at scale
  • Strong debugging and profiling skills
  • Deep understanding of performance engineering and systems optimization

5+ years of software engineering experience

  • BS, MS, or PhD in Computer Science or a related field
  • Experience with large-scale recommendation, ranking, generative AI, or foundation model systems
  • Familiarity with GPU architectures and performance analysis tools
  • Experience optimizing cloud infrastructure costs across large ML workloads

Preferred

  • Experience with machine learning infrastructure, training systems, or model serving platforms
  • Experience with distributed training frameworks such as PyTorch Distributed, Ray, Tensorflow, Spark

Pay

USD 230,000 - 322,000

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