Staff Machine Learning Engineer, ML Efficiency

• Build the infrastructure, tooling, and optimisation systems that enable ML engineers and researchers to train, evaluate, deploy, and operate models efficiently at scale. • Focus on improving developer productivity, reducing infrastructure costs, increasing hardware utilisation, and accelerating experimentation across Reddit's ML ecosystem. • Drive technical strategy for ML platform scalability, reliability, and cost efficiency.

• Hold a BS, MS, or PhD in Computer Science or a related field. • Bring 5+ years of software engineering experience. • Demonstrate strong proficiency in Python. • Have proficiency in at least one systems language such as Go, C++, Rust, or Java. • Have experience building distributed systems at scale. • Bring experience with machine learning infrastructure, training systems, or model serving platforms. • Demonstrate deep understanding of performance engineering and systems optimisation. • Have strong debugging and profiling skills.

• Have experience with large-scale recommendation, ranking, generative AI, or foundation model systems. • Bring experience with distributed training frameworks such as PyTorch Distributed, Ray, TensorFlow, or Spark. • Have familiarity with GPU architectures and performance analysis tools. • Have experience optimising cloud infrastructure costs across large ML workloads. • Bring contributions to internal platforms used by multiple ML teams. • Have experience building real-time ML inference applications.

• Design and build systems that improve the efficiency of ML training and inference workloads. • Develop tooling that helps ML engineers debug, profile, optimise, and monitor model performance. • Improve GPU and general resource utilisation through scheduling, resource management, caching, and workload optimisation. • 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. • Optimise 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.

• Access global benefit programmes that fit your lifestyle, from workspace to professional development to caregiving support. • Receive family planning support. • Access gender-affirming care. • Use mental health and coaching benefits. • Join the Group Personal Pension Scheme with employer match. • Access private medical and dental scheme. • Benefit from income replacement programmes. • Use the Bike to Work scheme. • Enjoy flexible vacation and paid volunteer time off. • Take generous paid parental leave.

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