AI Performance Optimization Engineer

Location: Remote
Compensation: Salary
Reviewed: Sun, May 17, 2026
This job expires in: 30 days

Job Summary

AI Performance Optimization Engineer, a full-time remote position focused on optimizing AI training and inference workloads for large neural network systems through performance engineering and collaboration with cross-functional teams.

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
  • Implement and tune quantization, sparsity, and pruning strategies to enhance model performance
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++
  • Hands-on experience optimizing deep learning workloads on modern GPUs
  • Deep understanding of distributed training and inference techniques

COMPLETE JOB DESCRIPTION

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