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Follow →Design, deploy, and optimize GPU compute infrastructure to support AI/ML workloads and high-performance computing in a remote-first environment.
Location: United States
Workplace: remote
Employment Type: full
Build and deploy AI/ML models to solve real-world problems for clients in a fully remote role.
Owns and validates GPU-enabled bare-metal infrastructure for AI/ML workloads, automating provisioning, diagnostics, and system bring-up while ensuring reliability and performance.
Build and run AI workloads on Google’s GKE, GPUs, and TPUs, then create demos and content to teach developers how to scale them efficiently.
Designs and automates secure, scalable cloud networks across AWS, Azure, and GCP, using Terraform, Kubernetes, and CI/CD to support enterprise infrastructure and hybrid connectivity.
Builds scalable serverless systems in AWS (Lambda, Glue, API Gateway) to manage education benefits, eligibility workflows, and AI-powered features like virtual assistants and RAG pipelines for Guild’s employer partners.
Senior Software Engineer designing and maintaining system software that enables high-performance communication between GPUs for AI and HPC workloads using C/C++, Linux, and networking fundamentals.