AI Performance Optimization Engineer
Location: Remote
Compensation: Salary
Reviewed: Thu, May 28, 2026
This job expires in: 30 days
Job Summary
Seeking a skilled AI Performance Optimization Engineer for a full-time remote position, responsible for maximizing throughput, minimizing latency, and reducing costs across training and inference workloads for large neural network 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
- 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 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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