As a Senior Research Engineer at Frontier AI & Robotics, you will play a crucial role in transforming innovative research into high-performance production systems. You will collaborate with scientists to build and optimize large-scale transformer models specifically for robotics applications. This position focuses on deep technical optimization and strategic input on model architecture decisions. You will leverage advanced tools and frameworks to tackle ambitious performance targets in real-world robotics scenarios.

• 5+ years of non-internship professional software development experience or a Bachelor's degree in computer science or equivalent.
• 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, tech lead, or leading an engineering team.
• Expertise in Python, PyTorch, and CUDA programming.
• Experience with TensorRT or similar ML optimization frameworks.
• Ability to optimize ML models for production.
• Experience working directly with research teams.
• Experience in ML infrastructure such as Pytorch, Megatron, TorchTitan, etc.
• Experience with ML compilers like ONNX Runtime or TVM.
• Experience with transformer model optimization or RL framework development.
• Background in performance profiling and optimization.

• Design, implement, and optimize distributed training systems that scale across thousands of GPUs and nodes.
• Develop high-performance optimizations to maximize throughput and efficiency.
• Develop reusable frameworks and libraries to improve training reproducibility, reliability, and scalability.
• Establish standards for reliability, maintainability, and security.
• Collaborate with researchers to influence model architectures for optimal hardware utilization.
• Develop comprehensive benchmarking frameworks to measure and optimize model performance.
• 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.
• Manage pre/post training runs and continue to improve system stability and throughput.

• 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.