Senior Software Development Engineer, Amazon

• Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale
• Bachelor's degree in computer science or equivalent
• 5+ years of non-internship professional software development experience
• 5+ years of programming with at least one software programming language experience
• 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
• Experience as a mentor, tech lead or leading an engineering team
• Strong expertise in Python, C++ and CUDA programming
• Experience with TensorRT or similar ML optimization frameworks
• Track record of optimizing ML models for production
• Expertise in NVIDIA's ML stack (cuDNN, CUDA Graph, etc.)

Desirable

• Join the next revolution in robotics at Amazon's Frontier AI & Robotics team, where you'll work alongside world-renowned AI pioneers like Pieter Abbeel, Rocky Duan, and Peter Chen to make breakthrough foundation models run at production scale
• As a Senior Machine Learning Engineer embedded in our science team, you'll be instrumental in transforming cutting-edge research into high-performance production systems
• You'll collaborate directly with scientists to optimize large-scale transformer architectures for robotics applications, leveraging your expertise in CUDA and TensorRT to achieve unprecedented inference efficiency at Amazon scale
• You'll leverage NVIDIA's acceleration stack and other compilation techniques to tackle ambitious performance targets, working at the intersection of large language models and real-world robotics applications
• Drive inference optimization strategies for large-scale foundation models using TensorRT, CUDA, and other NVIDIA tools
• Collaborate closely with scientists to influence model architectures for optimal hardware utilization
• Design and implement efficient compilation pipelines for complex transformer architectures
• Develop comprehensive benchmarking frameworks to measure and optimize model performance
• Build robust monitoring solutions to ensure reliable model serving at scale
• Explore and evaluate emerging optimization techniques including ONNX Runtime and other ML compilers
• Maintain high engineering standards through proper testing, documentation, and code review practices
• A day in the life:
• Optimize transformer blocks using custom CUDA kernels and TensorRT optimization techniques
• Partner with scientists to analyze model architectures and propose efficiency improvements
• Implement and benchmark various optimization strategies for large-scale models
• Debug performance bottlenecks using NVIDIA profiling tools
• Participate in technical discussions about new model architectures with the science team
• Design and maintain performance monitoring systems for production deployment
• Prototype new acceleration approaches using emerging compilation frameworks
• Our team, led by pioneering AI researchers Pieter Abbeel, Rocky Duan, and Peter Chen, is building the future of intelligent robotics through groundbreaking foundation models and end-to-end learned systems
• We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios
• At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up
• Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios
• We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations
• In this role, you'll balance deep technical optimization work with strategic input on model architecture decisions, ensuring our innovative robotics models are designed with performance in mind from the ground up