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Architect and build secure, scalable cloud and edge infrastructure for AI workloads. Implement IaC, Kubernetes with GPU support, CI/CD with security controls, observability, MLOps pipelines, disaster recovery, incident response, and mentor engineers while driving infrastructure standards and automation.

Lead the design and implementation of automated testing infrastructure, improve product quality, mentor junior engineers, and integrate tests into CI/CD pipelines.

The Network Engineer will design, implement, and maintain secure distributed AI infrastructure, ensuring high performance and reliability across various networks and devices while collaborating with cross-functional teams.

The Staff Machine Learning Engineer will lead the development of advanced AI models, collaborate with teams, conduct research, and mentor junior engineers.

Lead the development of AI systems integrating computer vision and language understanding, focusing on reinforcement learning and multimodal AI architectures.

As an R&D Software Engineer, you'll rapidly prototype AI technologies, translating theoretical research into practical implementations while collaborating with cross-functional teams.