Shield AI
Senior Staff Engineer, ML Ops (R4941)
San Diego, California · Senior Staff · Full-time · Posted Oct 20, 2026
About the job
Leads the design and development 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
- Design and implement AI platform capabilities for distributed training, simulation, evaluation, and deployment.
- Partner with ML researchers and engineering teams to turn evolving research workflows into scalable, self-service platform capabilities.
- Build and optimize GPU infrastructure, data and model lifecycle tools, and repeatable deployment solutions.
What they ask for
- Experience building Kubernetes-native AI or MLOps platforms for distributed machine-learning workloads.
- Deep understanding of PyTorch, 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 GPU scheduling concepts and large-scale AI workloads.
- Experience with Terraform and Helm, strong software engineering skills in Python and Golang, and collaboration with ML researchers.
Nice to have
- Experience with Ray, KAI, Slurm, or other distributed AI orchestration or GPU scheduling technologies.
- Experience with reinforcement learning, simulation-driven training, robotics, autonomy, edge deployment, classified or air-gapped environments, observability, or open-source infrastructure.
Tools
Kubernetes, PyTorch, Hugging Face Transformers, Terraform, Helm, Python, Golang, KAI
AI focus
Builds infrastructure and workflows for AI research, foundation model development, distributed training, reinforcement learning, simulation, evaluation, inference, and deployment.
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