Senior Staff Engineer, ML Ops (R4941)

📋 Description

• Lead the design and implementation of the AI Factory Reference Architecture, delivering a
• Partner with ML researchers to support training workflows, foundation models, reinforcement
• Design self-service AI development workflows for engineers to move from local experimentation to
• Build infrastructure to support distributed training, simulation, inference, and reinforcement
• Design and optimize shared GPU infrastructure across cloud and on-premises environments including
• Develop platform capabilities for dataset management, experiment tracking, artifact management

🎯 Requirements

• Experience building Kubernetes-native AI or MLOps platforms for distributed ML workloads.
• Deep understanding of AI training frameworks (PyTorch, Hugging Face Transformers) and distributed
• Experience operating GPU-accelerated infrastructure and distributed training systems.
• Strong knowledge of Kubernetes, Linux, networking, security, storage, and distributed systems.
• Experience with GPU scheduling concepts and large-scale AI workloads.
• Experience packaging/deploying cloud-native infrastructure using Terraform and Helm.

🎁 Benefits

• The AI Factory foundation for developing and deploying autonomy.
• Impact on researcher iteration speed, compute resource efficiency, and deployment readiness.
• Opportunity to work at the intersection of AI, distributed systems, Kubernetes, and defense with