Member of Technical Staff (AI Infrastructure Engineer)

📋 Description

• Design, deploy, and maintain scalable Kubernetes clusters for AI model inference and training
• Manage and optimize Slurm-based HPC environments for distributed training of large language models
• Develop robust APIs and orchestration systems for both training pipelines and inference services
• Implement resource scheduling and job management systems across heterogeneous compute environments
• Benchmark system performance, diagnose bottlenecks, and implement improvements across both training
• Build monitoring, alerting, and observability solutions tailored to ML workloads running on

🎯 Requirements

• Expert-level Kubernetes administration and YAML configuration management
• Proficiency with Slurm job scheduling, resource management, and cluster configuration
• Experience deploying and managing distributed training systems at scale (PyTorch)
• Deep understanding of container orchestration and distributed systems architecture
• Familiarity with LLM concepts and training processes; GPU resource optimization
• Experience operating large-scale Kubernetes deployments in production