Site Reliability Engineer (GPU & ML Infrastructure)

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Criteo is hiring a Senior Site Reliability Engineer for GPU & ML Infrastructure. The role involves designing, operating, and scaling infrastructure for machine learning training and inference workloads. Key technologies include Ray on Kubernetes and NVIDIA Triton Inference Server. Responsibilities include building scalable Ray clusters, developing self-service distributed computing platforms, optimizing inference platforms, and collaborating with ML engineers and data scientists. Candidates should have 5+ years in backend, SRE, or platform engineering with distributed systems, strong Kubernetes experience, hands-on GPU workload optimization, and software engineering skills in C#, Python, or Go. The position offers a hybrid work model with offices in Paris and Grenoble, France, and benefits including career development, health and wellness support, and competitive pay.