AI Performance Optimization Engineer

Job Summary

Focusing on optimizing AI training and inference pipelines, the full-time AI Performance Optimization Engineer will work remotely to enhance throughput, minimize latency, and reduce costs across large neural network systems while collaborating with cross-functional teams and mentoring junior engineers.

Key Responsibilities

• Profile and optimize end-to-end AI training and inference pipelines for throughput, latency, and cost
• Identify and eliminate bottlenecks across data loading, model compute, communication, and memory
• Drive compiler-level optimizations and collaborate with ML and platform engineering teams to embed best practices in standard pipelines

Required Qualifications

• Bachelor's or master's degree in computer science, Computer Engineering, or related field
• Six or more years of experience in performance engineering, ML systems, or HPC
• Strong proficiency in Python and C++
• Hands-on experience optimizing deep learning workloads on modern GPUs
• Deep understanding of distributed training and inference techniques