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Principal GPU/CUDA Engineer

AI Startup in Stealth
Mountain View, CA Full Time
POSTED ON 3/11/2025
AVAILABLE BEFORE 4/9/2025

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.

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