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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