Senior Staff Engineer, ML Ops (R4941)

The role

You will help design and build the AI Factory Reference Architecture, a Kubernetes-native platform for developing, training, evaluating and deploying AI systems. You will work with ML researchers, platform engineers and autonomy teams to build a developer experience for training and deploying modern AI models.

What you will do

• Lead design and implementation of the AI Factory Reference Architecture, a Kubernetes-native platform for AI development, distributed training, simulation, evaluation and deployment.
• Partner with ML researchers to support frameworks, foundation model development, reinforcement learning and distributed training.
• Design self-service AI development workflows from local experimentation to large-scale distributed execution.
• Build infrastructure for distributed training, simulation, inference and reinforcement learning workloads.
• Design and optimize shared GPU infrastructure across cloud and on-premises environments.
• Build platform capabilities for dataset management, experiment tracking, model versioning, evaluation, deployment and monitoring.
• Develop repeatable deployment solutions using Infrastructure as Code, supporting cloud, customer-managed, sovereign and air-gapped environments.
• Evaluate emerging AI infrastructure technologies and set architectural patterns.
• Work with AI researchers, autonomy teams, infrastructure engineers and product teams.

Required qualifications

• Experience building Kubernetes-native AI or MLOps platforms supporting distributed machine learning workloads.
• Deep understanding of AI training frameworks, including 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 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 closely with ML researchers to translate research workflows into scalable platform capabilities.

Nice to have

• Experience with Ray or other distributed AI orchestration frameworks.
• Experience with KAI, Slurm or other GPU scheduling technologies.
• Experience supporting reinforcement learning, simulation-driven training, robotics or autonomy workloads.
• Experience deploying and optimizing AI models for edge hardware.
• Experience designing infrastructure for classified, sovereign or air-gapped environments.
• Experience with observability technologies such as OpenTelemetry, Prometheus and Grafana.
• Experience contributing to or maintaining open-source infrastructure projects.

Benefits

• Full-time regular employees: bonus
• Full-time regular employees: benefits
• Full-time regular employees: equity
• Temporary employees: temporary benefits package, applicable after 60 days of employment

Before you apply

• All offers are contingent on a cleared background and possible reference check.
• Military fellows and part-time employees are not eligible for benefits.

About the company

Shield AI is a venture-backed defense-tech company that builds intelligent systems to protect service members and civilians. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation technologies.