Shield AI
Senior Staff Engineer, ML Ops (R4941)
San Mateo, California · Senior Staff · Full-time · Posted Oct 20, 2026
About the job
Leads the design and implementation of Shield AI’s Kubernetes-native AI Factory platform for developing, training, evaluating, and deploying AI systems across cloud, on-premises, sovereign, and air-gapped environments.
What you'll do
- Build platform capabilities for distributed AI training, simulation, inference, evaluation, deployment, and model lifecycle management.
- Partner with ML researchers and engineering teams to enable research workflows and improve the AI developer experience.
- Design shared GPU infrastructure and repeatable platform deployments, optimizing scheduling, reliability, and resource utilization.
What they ask for
- Experience building Kubernetes-native AI or MLOps platforms for distributed machine-learning workloads.
- Deep understanding of AI training frameworks, including PyTorch and Hugging Face Transformers, and distributed training techniques.
- Experience operating GPU-accelerated infrastructure and distributed training systems; strong understanding of Kubernetes, Linux, networking, security, storage, and distributed systems.
- Experience with Terraform and Helm, and strong software engineering skills in Python and Golang.
Nice to have
- Experience with Ray, KAI, Slurm, or other distributed AI orchestration or GPU scheduling technologies.
- Experience with reinforcement learning, simulation, robotics, autonomy, edge AI, classified or air-gapped infrastructure, observability tools, or open-source infrastructure projects.
Tools
Kubernetes, PyTorch, Hugging Face Transformers, Terraform, Helm, Python, Golang, Ray
AI focus
Builds infrastructure and developer workflows for AI research, distributed training, reinforcement learning, simulation, evaluation, inference, and deployment, including autonomy systems.
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