A company is looking for an AI Performance Engineer to optimize training and multi-node inference across advanced networking systems.
Key Responsibilities :
Own end-to-end performance for distributed AI workloads across multi-node clusters and diverse fabrics
Benchmark, characterize, and tune open-source & industry workloads on current and future hardware
Design and optimize distributed serving topologies and validate inferencing optimizations
Required Qualifications :
B.S. in CS / EE / CE / Math or related field
5-7+ years of experience running AI / ML at cluster scale
Proven ability to analyze AI benchmarks and identify scaling bottlenecks
Hands-on experience with distributed training and inference architectures
Familiarity with network architectures and performance tuning in Linux systems
Performance Engineer • Lubbock, Texas, United States