Senior Staff Engineer — AI Platform & Distributed Training

Shieldai; San Mateo (CA); On-site; USD 210,000 - 320,000; Full time

Benefits offered by this job

Bonus

Benefits

Equity

Job summary

Shield AI seeks a Senior Staff Engineer to define and build the AI Factory Reference Architecture, a Kubernetes-native platform for developing, training, evaluating, and deploying next-generation AI systems.

You will partner with ML researchers, platform engineers, and autonomy teams to deliver a best-in-class developer experience, balancing researcher productivity with platform simplicity and reliability. The role spans cloud, on-prem, and air-gapped environments.

Qualifications

• Strong software engineering background in Python/Golang and cloud-native tech.
• Experience with distributed AI systems and GPU scheduling.
• Familiarity with AI training/inference tooling (PyTorch, Transformers) preferred.

Responsibilities

• Design the AI Factory Reference Architecture as a Kubernetes-native platform for AI development, training, evaluation, and deployment.
• Enable researchers by building scalable training workflows and developer-friendly tooling.
• Collaborate with ML researchers, platform engineers, and autonomy teams to improve platform usability and performance.
• Lead infrastructure for distributed training, simulation, inference, and reinforcement learning at scale.
• Ensure security, observability, and maintainability across cloud, on-prem, and air-gapped environments.

Skills

Python

Golang

Kubernetes

Cloud-native technologies

Distributed AI

Ray or orchestration frameworks

GPU scheduling

Edge deployment

Education

Bachelor's degree in CS/Engineering

Tools

Terraform

Helm

OpenTelemetry

Prometheus

Grafana

Job description

Shield AI seeks a Senior Staff Engineer to define and build the AI Factory Reference Architecture, a Kubernetes-native platform for developing, training, evaluating, and deploying next-generation AI systems.

You will partner with ML researchers, platform engineers, and autonomy teams to deliver a best-in-class developer experience, balancing researcher productivity with platform simplicity and reliability. The role spans cloud, on-prem, and air-gapped environments.