Staff Machine Learning Engineer, ML Efficiency

• Join the ML Efficiency team, building the infrastructure, tooling and optimisation systems that let ML engineers and researchers 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. • Lead cross-functional initiatives and drive technical strategy for ML platform scalability, reliability and cost efficiency. • Work at Staff level on distributed training infrastructure, data pipelines and model serving architectures. • Work fully remotely from anywhere in the UK or the Netherlands.

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

• Bring 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. • Bring familiarity with GPU architectures and performance analysis tools. • Bring experience optimising cloud infrastructure costs across large ML workloads. • Bring contributions to internal platforms used by multiple ML teams, or 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. • Lead cross-functional initiatives and drive technical strategy for ML platform scalability, reliability and cost efficiency.

• Join a flexible-first workforce working remotely from anywhere in the UK or the Netherlands. • Receive a Group Personal Pension Scheme with employer match, plus private medical and dental cover. • Take flexible vacation and paid volunteer time off, with generous paid parental leave. • Access family planning support, gender-affirming care, and mental health and coaching benefits. • Benefit from income replacement programs and a Bike to Work scheme.

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