Principal GPU/CUDA Engineer

Principal CUDA Software Engineer We are looking for a Principal CUDA Software Engineer to design and optimize GPU-based solutions for demanding AI/ML workloads. This role requires deep expertise in parallel computing, low-level hardware interactions, and high-level software frameworks. As a Principal CUDA Software Engineer , you will be responsible for ensuring maximum efficiency and performance in large-scale AI deployments. This opportunity is with a rapidly growing company dedicated to advancing AI and parallel computing. The leadership team has a strong track record in delivering cutting-edge technologies, with a focus on efficient GPU architectures. The environment prioritizes autonomy, rapid iteration, and direct engineer impact on product development. This is a place where a Principal CUDA Software Engineer can make a tangible difference in shaping next-generation AI systems. As a Principal CUDA Software Engineer , you will work closely with hardware engineers to fine-tune performance at the driver and runtime levels. Your focus will be on optimizing CUDA-based components, ensuring seamless AI/ML functionality, and maintaining critical libraries, toolchains, and frameworks. Your expertise in benchmarking, profiling, and analysis will play a key role in delivering high-performance GPU solutions. This is a highly technical role that directly impacts the efficiency and scalability of AI-driven workloads. What We Can Offer You A role at the forefront of next-generation AI and GPU computing Competitive salary, equity, and comprehensive benefits A collaborative and engineering-focused environment that values technical excellence Opportunities for professional development through training and industry conferences Direct influence on architectural decisions and product evolution Key Responsibilities As the Principal CUDA Software Engineer , develop and optimize CUDA-based components for AI/ML workloads Work closely with hardware engineers to implement low-level performance improvements Maintain drivers, runtime libraries, and compiler toolchains for GPU-based AI solutions Conduct benchmarking, profiling, and code path analysis to optimize performance Provide technical leadership and mentor junior engineers in CUDA development Relevant keywords: CUDA, GPU computing, parallel processing, AI acceleration, compiler toolchains, runtime libraries, performance optimization, benchmarking, low-level programming.