Shield AI · San Diego, California
Skills: Python, Docker
Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai https://shield.ai/. Follow Shield AI on LinkedIn https://www.linkedin.com/company/shield-ai, X https://x.com/shieldaitech, Instagram https://www.instagram.com/shieldai, and YouTube https://www.youtube.com/@ShieldAI. JOB DESCRIPTION: Machine-learning engineers need reliable access to GPUs to train and evaluate models. Shield AI’s AI Factory provides shared compute and development tools for these workflows, both for our engineers and for customer deployments. We are looking for a Platform Engineer to make that compute platform easier to use, more reliable and more efficient. You will write software, improve how teams share GPUs, help developers troubleshoot workloads and use performance data to guide capacity growth. This is a hands-on software and platform engineering role. What you'll do: - - Build and maintain the software and configuration that let developers run GPU workloads on Kubernetes. - Design quotas, scheduling priorities, permissions and isolation so multiple teams can share compute predictably. - Automate deployment and upgrades of GPU services, including Run:ai, with infrastructure as code and tools such as Terraform and Helm. - Investigate why jobs wait, fail or run slowly, and fix recurring scheduling, configuration, storage and networking problems. - Build diagnostics that connect queue times, GPU utilization, memory requirements and training throughput to the developer’s experience. - Benchmark representative workloads and recommend when to add GPU capacity, how much to add and which hardware…
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