This role is focused on building distributed inference support for PyTorch in the Neuron SDK, aimed at optimizing machine learning models for AWS's custom ML accelerators. The High-Performance Inference Systems & Acceleration team emphasizes collaboration across software, hardware, and machine learning systems to enhance performance and efficiency. Engineers in this role will work closely with customers to ensure optimal performance of their machine learning workloads. The position offers a unique opportunity to innovate in a dynamic and experimental environment.

• Bachelor's degree in computer science or equivalent.
• 5+ years of non-internship professional software development experience.
• 5+ years of programming experience with at least one software programming language.
• 5+ years of experience leading design or architecture of new and existing systems.
• Experience as a mentor or tech lead in an engineering team.
• Fundamentals of machine learning and LLMs, including architecture, training, and inference lifecycles.
• Software development experience in C++ and Python.
• Strong understanding of system performance, memory management, and parallel computing principles.
• 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, implementation, and performance profiling.
• Build infrastructure to 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.