Machine Learning - Compiler Engineer, Annapurna Labs

AWS Machine Learning accelerators team at Annapurna Labs is seeking a Machine Learning Compiler Engineer to join their innovative team. The role focuses on developing and scaling compilers for handling the world's largest ML workloads. The team is responsible for AWS Neuron, a deep learning compiler stack that converts neural network descriptions from frameworks like TensorFlow, PyTorch, and MXNET into executable code.

The position offers an opportunity to work with cutting-edge technology in ML acceleration, specifically with AWS Inferentia chip that delivers best-in-class ML inference performance and Trainium for ML training. You'll be part of a team comprising some of the brightest minds in engineering, research, and product development.

The role combines hands-on development with strategic thinking, requiring both technical expertise in compiler optimization and an understanding of machine learning systems. You'll work closely with AWS ML services teams, contribute to pre-silicon design, and help bring new products and features to market.

Amazon offers a comprehensive benefits package, including competitive base pay ranging from $129,300 to $223,600 depending on location, plus equity and sign-on payments. The company emphasizes work-life balance, offering flexible working hours and a supportive team environment focused on knowledge sharing and mentorship.

The ideal candidate will have strong programming skills in C++ or Python, experience with compiler architecture and optimization, and a passion for machine learning technology. While ML and AI accelerator experience is preferred, it's not mandatory. This role offers significant growth potential and the opportunity to impact the future of cloud-based machine learning infrastructure.