AI Infra Engineer
Skills
- Expert-level Kubernetes administration and YAML configuration
- Proficiency with Slurm job scheduling and cluster configuration
- Python and C++ programming focused on systems and infrastructure automation
- Hands-on experience with ML frameworks such as PyTorch in distributed training
- Strong understanding of networking, storage, and compute resource management
- Experience developing APIs and managing distributed batch and real-time workloads
- Solid debugging and monitoring skills with observability tools for containerized environments
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 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
- Respond swiftly to system outages and collaborate across teams to maintain high uptime
- Optimize cluster utilization and implement autoscaling strategies for dynamic workloads
Benefits
- Comprehensive health, dental, and vision insurance for employees and dependents
- 401(k) retirement plan
- Equity compensation in addition to base salary
Average salary estimate
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