AI Performance Optimization Engineer

Job Summary

Focusing on optimizing AI training and inference workloads, the full-time AI Performance Optimization Engineer will work remotely to enhance throughput, minimize latency, and reduce costs across large neural network systems.

Key Responsibilities

• Profile and optimize end-to-end AI training and inference pipelines for performance metrics
• Identify and eliminate bottlenecks in data loading, model compute, and memory
• Drive compiler-level optimizations and collaborate with engineering teams to implement best practices

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related field
• Six or more years of experience in performance engineering, ML systems, or HPC
• Strong proficiency in Python and C++ with hands-on experience optimizing deep learning workloads
• Deep understanding of distributed training and inference techniques
• Experience with profiling tools across CPU, GPU, and distributed systems