AI Infra Engineer

REQUIRED SKILLS

• Expert-level Kubernetes administration and YAML configuration management
• Proficiency with Slurm job scheduling, resource management, and cluster configuration
• Python and C++ programming with focus on systems and infrastructure automation
• Hands-on experience with ML frameworks such as PyTorch in distributed training contexts
• Strong understanding of networking, storage, and compute resource management for ML workloads
• Experience developing APIs and managing distributed systems for both batch and real-time workloads
• Solid debugging and monitoring skills with expertise in observability tools for containerized environments

PREFERRED SKILLS

• Experience with Kubernetes operators and custom controllers for ML workloads
• Advanced Slurm administration including multi-cluster federation and advanced scheduling policies
• Familiarity with GPU cluster management and CUDA optimization
• Experience with other ML frameworks like TensorFlow or distributed training libraries
• Background in HPC environments, parallel computing, and high-performance networking
• Knowledge of infrastructure as code (Terraform, Ansible) and GitOps practices
• Experience with container registries, image optimization, and multi-stage builds for ML workloads

REQUIRED EXPERIENCE

• Demonstrated experience managing large-scale Kubernetes deployments in production environments
• Proven track record with Slurm cluster administration and HPC workload management
• Previous roles in SRE, DevOps, or Platform Engineering with focus on ML infrastructure
• Experience supporting both long-running training jobs and high-availability inference services
• Ideally, 3-5 years of relevant experience in ML systems deployment with specific focus on cluster orchestration and resource management