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Posted 2 hours ago

Staff Machine Learning Engineer, ML Efficiency

at Redditinc

NetherlandsRemote

Responsibilities

  • Design and build systems that improve the efficiency of ML training and inference workloads.
  • Develop tooling that helps ML engineers debug, profile, optimize, and monitor model performance.
  • Improve GPU and general resource utilization through scheduling, resource management, caching, and workload optimization.
  • Build benchmarking frameworks and performance dashboards for training and serving systems.
  • Optimize distributed training infrastructure, data pipelines, and model serving architectures.
  • Lead cross-functional initiatives that improve the productivity of Reddit ML engineers.
  • Drive technical strategy for ML platform scalability, reliability, and cost efficiency.

Requirements

  • With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information.
  • The ML Efficiency team builds the infrastructure, tooling, and optimization systems that enable machine learning engineers and researchers to train, evaluate, deploy, and operate models efficiently at scale.
  • We focus on improving developer productivity, reducing infrastructure costs, increasing hardware utilization, and accelerating experimentation across the company’s ML ecosystem. Responsibilities
  • Partner with ML researchers and product teams to identify bottlenecks and drive performance improvements.
  • BS, MS, or PhD in Computer Science or a related field.
  • Strong proficiency in Python
  • Profiency in at least one systems language (Go, C++, Rust, or Java) preferred •
  • Experience with machine learning infrastructure, training systems, or model serving platforms.
  • Deep understanding of performance engineering and systems optimization.
  • Experience with large-scale recommendation, ranking, generative AI, or foundation model systems. •
  • Experience with distributed training frameworks such as PyTorch Distributed, Ray, Tensorflow, Spark
  • Familiarity with GPU architectures and performance analysis tools. •
  • Experience optimizing cloud infrastructure costs across large ML workloads.
  • Contributions to internal platforms used by multiple ML teams. •
  • Experience with building real time ML inference applications
  • ML engineers can move from idea to experiment faster.
  • Platform reliability improves as ML workloads scale.
  • In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI).

Experience

  • 5+ years of software engineering experience.

Benefits

  • Gender-Affirming Care
  • Private Pension plan with Employer-matching
  • Flexible Vacation & Paid Volunteer Time Off
  • Generous Paid Parental Leave

Contact

  • For more information, visit www.redditinc.com .

Additional details

  • It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet.
  • Location: Reddit has a flexible first workforce. Don't live near our office? No worries: you can work remotely from anywhere in the UK or the Netherlands. About the Team
  • Experience building distributed systems at scale. •
  • Strong debugging and profiling skills. Preferred •
  • Training and inference costs decrease, performance increases, while model quality is maintained or improved.
  • Teams spend less time managing infrastructure and more time building models.
  • Average recommendation model size increases. Benefits:
  • Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
  • You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.
  • Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures.

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