ML Compiler Engineer, Annapurna Labs

The AWS Neuron Compiler team is seeking skilled compiler engineers to develop a state-of-the-art deep learning compiler stack. This role involves optimizing application models across diverse domains, including Large Language and Vision, from frameworks like PyTorch, TensorFlow, and JAX. You'll work with custom-built Machine Learning accelerators such as Inferentia/Trainium, contributing to AWS's innovation in advanced ML capabilities and Generative AI.

As an ML Compiler engineer, you'll design, develop, and optimize compiler features, tackling crucial challenges in compiler technology and deep-learning systems software. You'll collaborate with cross-functional teams to ensure system-wide performance optimization.

Key responsibilities include:

• Solving challenging technical problems at every layer of the stack
• Designing, implementing, testing, deploying, and maintaining innovative software solutions
• Researching implementations for the best possible customer experiences
• Building high-impact solutions for a large customer base
• Participating in design discussions, code reviews, and communicating with stakeholders
• Working cross-functionally to drive business decisions with technical input

The role offers opportunities to work on instruction scheduling, memory allocation, data transfer optimization, graph partitioning, parallel programming, code generation, Instruction Set Architectures, new hardware bring-up, and hardware-software co-design.

You'll be part of a team that values knowledge-sharing, mentorship, and career growth, working in a startup-like environment focused on the most impactful projects.

This position may involve exposure to Amazon's growing suite of generative AI services and other cutting-edge cloud computing offerings across the AWS portfolio.