AI Optimization Engineer

📋 Description

• Optimize training and inference workloads to maximize throughput, minimize latency, and improve
• Analyze and improve performance across the full technology stack, including GPU kernels, memory
• Profile CPU, GPU, and distributed workloads to identify bottlenecks and use quantitative analysis
• Design and implement performance improvements using Python, C++, and relevant AI systems
• Optimize distributed training and inference architectures, including model parallelism
• Evaluate and implement model compression techniques while carefully considering their impact on

🎯 Requirements

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related technical
• 6+ years of professional experience in performance engineering, machine learning systems
• Strong programming proficiency in Python and C++, with the ability to develop production-quality
• Hands-on experience optimizing deep learning workloads on modern GPU architectures.
• Deep understanding of distributed training and inference techniques, including parallelism
• Experience using profiling and instrumentation tools across CPU, GPU, and distributed environments.

🎁 Benefits

• $100,000 annual salary for this full-time direct W2 position.
• 100% remote work within the United States.
• Opportunity to work on challenging AI optimization and high-performance computing problems.
• Exposure to large-scale neural networks, modern GPU architectures, distributed systems, and