As a Software Engineer II - AI/ML at Amazon Web Services, you will focus on optimizing machine learning models and frameworks for deployment on custom ML hardware accelerators. You will work within the Model Enablement team, which emphasizes collaboration and continuous learning while supporting customers in achieving optimal performance on their models. This role involves designing, developing, and tuning distributed inference solutions for large language models, contributing to the future of AI acceleration technology. You will collaborate with cross-functional teams to deliver state-of-the-art inference capabilities for Generative AI applications.

• 3+ years of non-internship professional software development experience
• 3+ years of non-internship design or architecture experience of new and existing systems
• 1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications
• Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field
• Experience debugging, profiling, and implementing best software engineering practices in large-scale systems
• Experience with Machine Learning and Large Language Model fundamentals
• Knowledge of Python and/or C++ programming
• Strong understanding of system performance, memory management, and parallel computing principles
• Experience with CUDA kernels or ML/low-level kernels
• Experience with PyTorch, JIT compilation, and AOT tracing

• 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 architectures.
• Understand and produce Neuron Kernel Interface kernels, and design and implement high-performance kernels 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 and share findings with internal and external stakeholders.

• 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.