Summary
Matthew Sklar is a Machine Learning Engineer with a decade of experience building scalable, production-grade systems and ML research implementations. Now at Amazon, he transitioned from designing high-throughput AWS services at Amazon Music to applying ML expertise across production workloads, bringing strong ownership of CI/CD, monitoring, and large-scale ETL pipelines. His academic work at Georgia Tech produced peer-reviewed robotics and multi-agent RL research—shipping CUDA-optimized PyTorch training that sped experiments up to 8x and graph-attention communication models robust to transit loss. Comfortable across Python, C++, ROS, and cloud infrastructure, he blends deep research rigor with pragmatic engineering to move models from lab prototypes into highly available systems. Based in New York, he has a track record of turning complex algorithmic ideas into reliable, deployable software.
11 years of coding experience
4 years of employment as a software developer
Master's degree, Computer Science, Master's degree, Computer Science at Georgia Institute of Technology
English, Hebrew