Member of Technical Staff (AI Infrastructure Engineer)
Perplexity · San Francisco, CA · AI
About this role
Perplexity is hiring a staff-level Staff Engineer in the software engineering function based in San Francisco, CA. The posting calls out experience with CUDA, Kubernetes, Terraform, Ansible. Compensation is listed at $220,000–$405,000 per year.
- Role
- Staff Engineer
- Function
- software engineering
- Level
- staff
- Track
- Tech leadership
- Employment
- Full-time
- Location
- San Francisco, CA
- Department
- AI
- Posted
- Apr 13, 2026
More roles at Perplexity
Job description
from Perplexity careersWe are looking for an AI Infra engineer to join our growing team. We work with Kubernetes, Slurm, Python, C++, PyTorch, and primarily on AWS. As an AI Infrastructure Engineer, you will be partnering closely with our Inference and Research teams to build, deploy, and optimize our large-scale AI training and inference clusters
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 across both training and inference infrastructure
Build monitoring, alerting, and observability solutions tailored to ML workloads running on Kubernetes and Slurm
Respond swiftly to system outages and collaborate across teams to maintain high uptime for critical training runs and inference services
Optimize cluster utilization and implement autoscaling strategies for dynamic workload demands
Qualifications
Strong expertise in Kubernetes administration, including custom resource definitions, operators, and cluster management
Hands-on experience with Slurm workload management, including job scheduling, resource allocation, and cluster optimization
Experience with deploying and managing distributed training systems at scale
This is an excerpt. Read the full job description on Perplexity careers →