Perplexity
Member of Technical Staff (AI Infrastructure Engineer)
$220K–$405K
San Francisco +1 · Staff · Full-time · Posted Apr 13, 2026
- Location
- San Francisco
Palo Alto - Experience
- Ideally, 3-5 years of relevant experience in ML systems deployment, focused on cluster orchestration and resource management; other required experience is stated without a year count.
About the job
Build, deploy, and optimize large-scale AI training and inference infrastructure in partnership with Inference and Research teams.
What you'll do
- Design and maintain Kubernetes clusters and Slurm environments for AI training and inference.
- Develop APIs, orchestration, scheduling, monitoring, and resource-management systems for ML workloads.
- Benchmark and improve infrastructure performance, reliability, and cluster utilization.
What they ask for
- Expert Kubernetes administration and YAML configuration management.
- Proficiency with Slurm scheduling, resource management, and cluster configuration.
- Python and C++ programming, plus hands-on PyTorch experience in distributed training.
- Production experience managing large-scale Kubernetes deployments and Slurm/HPC workloads.
Nice to have
- Kubernetes operators and custom controllers for ML workloads.
- CUDA optimization, infrastructure as code (Terraform, Ansible), or GitOps practices.
Pay
$220K – $405K (base salary)
Tools
Kubernetes, Slurm, Python, C++, PyTorch, AWS, TensorFlow, Terraform
AI focus
Infrastructure for large-scale AI model training and inference, including distributed LLM training and GPU cluster optimization.
Model-written summary · the original posting is authoritative