Shield AI
Senior Staff Engineer, ML Ops (R4941)
$233K–$350K
San Diego, California · On-site · Senior Staff · Full-time · Posted May 14, 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, sovereign, and air-gapped environments.
What you'll do
- Build platform infrastructure for distributed AI training, simulation, inference, evaluation, and deployment.
- Partner with ML researchers and engineering teams to support research workflows and improve developer experience.
- Design GPU infrastructure and repeatable platform deployments, including resource scheduling and model lifecycle capabilities.
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 Terraform and Helm; strong software engineering skills in Python and Golang.
Nice to have
- Experience with Ray or other distributed AI orchestration frameworks, and GPU scheduling technologies such as KAI or Slurm.
- Experience with autonomy, reinforcement learning, edge AI, air-gapped environments, observability technologies, or open-source infrastructure.
Pay
USD 233,000–350,000 per-year-salary (base salary)
Tools
Kubernetes, PyTorch, Hugging Face Transformers, Terraform, Helm, Python, Golang, KAI
AI focus
Builds infrastructure and developer workflows for AI research and model development, including distributed training, reinforcement learning, simulation, evaluation, inference, and deployment.
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