AI Performance Optimization Engineer

Location: Remote
Compensation: Salary
Reviewed: Sat, May 16, 2026
This job expires in: 29 days

Job Summary

AI Performance Optimization Engineer, responsible for optimizing AI training and inference workloads in a full-time remote position, requiring extensive experience in performance engineering and deep learning systems.

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 reduce model footprint and accelerate inference
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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