Shield AI
Senior Staff Engineer, ML Ops (R4941)
$280K–$420K
San Mateo, California · On-site · Senior Staff · Full-time · Posted Aug 31, 2026
About the job
Leads the design and implementation of a Kubernetes-native AI platform for developing, training, evaluating, and deploying AI systems across cloud, on-premises, and air-gapped environments.
What you'll do
- Build the AI Factory platform and infrastructure for distributed training, simulation, inference, and deployment.
- Partner with ML researchers and engineering teams to support AI workflows and improve developer experience.
- Develop GPU infrastructure, model-lifecycle capabilities, and repeatable platform 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.
- Experience with Kubernetes, Terraform, Helm, 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, air-gapped infrastructure, or observability tools.
Pay
USD 280,000–420,000 (per-year-salary) — base salary
Tools
Kubernetes, PyTorch, Hugging Face Transformers, Terraform, Helm, Python, Golang, KAI
AI focus
Builds infrastructure enabling AI model development, distributed training, simulation, evaluation, inference, and deployment, including support for foundation models and reinforcement learning.
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