Member of Technical Staff (AI Infrastructure Engineer)

Responsibilities

• Design, deploy, and maintain scalable Kubernetes clusters for AI model inference and training workloads
• 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
• Build monitoring, alerting, and observability solutions tailored to ML workloads
• Optimize cluster utilization and implement autoscaling strategies

Requirements

• Expert-level Kubernetes administration and YAML configuration management
• Proficiency with Slurm job scheduling and resource management
• Proficiency in Python and C++ for systems and infrastructure automation
• Hands-on experience with PyTorch in distributed training contexts
• Experience managing large-scale Kubernetes deployments in production
• Proven track record with Slurm cluster administration and HPC workload management
• 3-5 years of relevant experience in ML systems deployment

Preferred Qualifications

• Experience with Kubernetes operators and custom controllers for ML workloads
• Advanced Slurm administration including multi-cluster federation
• Familiarity with GPU cluster management and CUDA optimization
• Knowledge of Infrastructure as Code (Terraform, Ansible) and GitOps
• Experience with container registries and image optimization for ML workloads