machine learning engineer for ML infrastructure

Reddit is a community of communities built around shared interests, passion, and trust. It hosts open conversations across more than 100,000 active communities and serves approximately 130 million daily active unique visitors.

• Design and build systems that improve the efficiency of ML training and inference workloads;
• Develop tooling for debugging, profiling, optimizing, and monitoring model performance;
• Improve GPU and general resource utilization through scheduling, resource management, caching, and workload optimization;
• Partner with ML researchers and product teams to identify bottlenecks and drive performance improvements;
• 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.

• BS, MS, or PhD in Computer Science or a related field;
• 5+ Years of software engineering experience;
• Strong proficiency in Python;
• Experience building distributed systems at scale;
• Experience with machine learning infrastructure, training systems, or model serving platforms;
• Deep understanding of performance engineering and systems optimization;
• Strong debugging and profiling skills;
• Nice to have: Proficiency in at least one systems language (Go, C++, Rust, or Java), 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 building real-time ML inference applications.

• Remote work is available from anywhere in the UK or the Netherlands;
• Global benefit programs covering workspace, professional development, and caregiving support;
• Family Planning Support;
• Gender-Affirming Care;
• Mental Health & Coaching Benefits;
• Group Personal Pension Scheme with Employer match;
• Private Medical and Dental Scheme;
• Income Replacement Programs;
• Bike to Work scheme;
• Flexible Vacation & Paid Volunteer Time Off;
• Generous Paid Parental Leave;
• Interviews may be recorded, transcribed, and summarized by AI in select roles and locations, with an option to opt out before scheduled interviews.