Senior Staff AI Platform Engineer (MLOps)

Shield; San Mateo (CA); On-site; USD 180,000 - 280,000; Full time

Job summary

Shield AI seeks a Senior Staff Engineer to shape and build the AI Factory Reference Architecture, a Kubernetes-native platform for AI development, distributed training, simulation, evaluation, and deployment. You will work closely with ML researchers, platform engineers, and autonomy teams to deliver an exceptional developer experience.

You will balance researcher productivity, platform simplicity, operational excellence, and long-term maintainability while hands-on across stack.

Qualifications

• Experience building Kubernetes-native AI or MLOps platforms supporting distributed machine learning workloads.
• Deep understanding of modern AI training frameworks, including PyTorch and Hugging Face Transformers.
• 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 packaging and deploying cloud-native infrastructure using Terraform and Helm.
• Strong software engineering skills in Python and Golang and modern cloud-native technologies.
• Experience collaborating with ML researchers to translate research workflows into scalable platform capabilities.

Responsibilities

• Lead the design and implementation of the Kubernetes-native AI Factory Reference Architecture for development, training, simulation, evaluation, and deployment.
• Partner with ML researchers to support evolving training workflows and frameworks.
• Design self-service AI development workflows enabling local experiments to large-scale distributed execution.
• Build infrastructure for distributed training, simulation, inference, and reinforcement learning workloads with scalable orchestration and scheduling.
• Design shared GPU infrastructure across cloud and on-prem environments for improved utilization.
• Build platform capabilities for dataset management, experiment tracking, artifact management, model versioning, evaluation, deployment, and monitoring.
• Develop repeatable deployment and lifecycle management solutions using Infrastructure as Code for cloud, customer-managed, sovereign, and air-gapped environments.
• Evaluate emerging AI infrastructure technologies and define architectural patterns balancing scalability and maintainability.
• Collaborate across AI researchers, autonomy teams, and product teams to evolve the platform with customer needs.

Skills

Kubernetes-native AI

MLOps platforms

Distributed training

PyTorch

Hugging Face Transformers

Kubernetes

Linux

Networking

Terraform

Helm

Python

Golang

Open-source tooling

Tools

Ray

Slurm

Job description

Shield AI seeks a Senior Staff Engineer to shape and build the AI Factory Reference Architecture, a Kubernetes-native platform for AI development, distributed training, simulation, evaluation, and deployment. You will work closely with ML researchers, platform engineers, and autonomy teams to deliver an exceptional developer experience.

You will balance researcher productivity, platform simplicity, operational excellence, and long-term maintainability while hands-on across stack.