Deep Learning Compiler Engineer II, AWS Neuron, Annapurna Labs

AWS is seeking a Deep Learning Compiler Engineer II to join their innovative Neuron team, working at the intersection of machine learning, high-performance computing, and distributed architectures. The role focuses on developing the AWS Neuron SDK, which optimizes neural net model performance on AWS Inferentia and Trainium custom chips.

The position offers a unique opportunity to work on cutting-edge technology that democratizes access to deep learning infrastructure. As a senior compiler engineer, you'll be responsible for architecting and implementing critical features, publishing research, and mentoring other engineers. The role involves working with AWS's custom silicon solutions and scaling compilers to handle the world's largest ML workloads.

AWS Neuron SDK is a comprehensive solution including a compiler, runtime, and debugger, integrated with major frameworks like TensorFlow, PyTorch, and MXNet. The team operates in an innovative environment where experimentation and invention are encouraged, working in small, agile teams despite the large scale of the projects.

The position offers excellent work-life balance with flexible working hours and a strong emphasis on personal development. AWS provides a supportive, inclusive culture with ten employee-led affinity groups and various learning opportunities, including diversity conferences and race/ethnicity conversations. The team values knowledge sharing and mentorship, making it an ideal environment for professional growth.

Key responsibilities include pre-silicon design participation, bringing new products to market, and partnering with AWS ML services teams. While a background in machine learning and AI accelerators is preferred, it's not mandatory. The role requires strong technical communication skills and the ability to work independently while collaborating effectively with various teams.

This position represents an opportunity to work on innovative products that are shaping the future of deep learning infrastructure while being part of a supportive team that values both technical excellence and personal growth. The role combines hands-on technical work with strategic thinking, making it ideal for engineers who want to make a significant impact in the field of machine learning infrastructure.