The role focuses on developing and optimizing machine learning models and frameworks for deployment on Amazon's custom ML hardware accelerators, Trainium and Inferentia. The Inference Enablement and Acceleration team emphasizes collaboration and innovation, working closely with customers to enhance their machine learning workloads. Engineers will engage in low-level optimization and system architecture while contributing to the future of AI acceleration technology. This position offers a unique opportunity to work at the intersection of machine learning, high-performance computing, and distributed architectures.

• 3+ years of non-internship professional software development experience
• Bachelor's degree or equivalent in Computer Science
• 3+ years of experience in design or architecture of new and existing systems
• Fundamentals of Machine learning and LLMs, their architecture, training and inference lifecycles
• Software development experience in C++ and Python
• Strong understanding of system performance, memory management, and parallel computing principles
• Familiarity with PyTorch, JIT compilation, and AOT tracing
• Experience with online/offline inference serving in production environments
• Deep understanding of computer architecture and operating systems

• Design, develop, and optimize machine learning models and frameworks for deployment on custom ML hardware accelerators.
• Participate in all stages of the ML system development lifecycle including architecture design and performance profiling.
• Build infrastructure to systematically analyze and onboard multiple models with diverse architecture.
• Design and implement high-performance kernels and features for ML operations.
• Analyze and optimize system-level performance across multiple generations of Neuron hardware.
• Conduct detailed performance analysis using profiling tools to identify and resolve bottlenecks.
• Implement optimizations such as fusion, sharding, tiling, and scheduling.
• Conduct comprehensive testing, including unit and end-to-end model testing.
• Work directly with customers to enable and optimize their ML models on AWS accelerators.
• Collaborate across teams to develop innovative optimization techniques.

• Employees at Amazon are often offered comprehensive health benefits—including multiple medical plan options (no pre-existing condition exclusions, 100% covered in-network preventive care), dental and vision plans, a 24/7 medical advice line from day one, expert second-opinion services, and broad mental-health support with several free counseling sessions (including pediatric). Financial wellness typically includes a 401(k) with company match (up to 2%), Restricted Stock Units (equity), FSAs, an emergency savings program, product and partner discounts, and even college-savings and home-purchase programs. Overall, the package is designed to support employees and their families’ health, finances, and day-to-day life.