Developer Technology Engineer - AI

NVIDIA NVIDIA · Semiconductors · Seoul, South Korea

NVIDIA is seeking an AI Developer Technology Engineer to collaborate with developers, optimize AI workloads on GPUs, and research innovative AI techniques. The role involves analyzing and optimizing performance on current and next-generation GPU architectures, with a focus on multi-modal model training or post-training.

What you'd actually do

  1. Collaborating closely with key application developers to understand and address their current and future challenges. Developing and optimizing core parallel algorithms and data structures, providing top solutions with GPUs through reference code and direct app contributions.
  2. Working intimately with diverse groups at NVIDIA including architecture, research, libraries, tools, and system software teams. Your insights will influence the development of next-generation architectures, software platforms, and programming models by investigating their impact on application performance and developer efficiency.
  3. Researching and developing innovative techniques in AI. You'll conduct comprehensive analysis and optimization to ensure the best possible performance on current and next-generation GPU architectures.

Skills

Required

  • MS or PhD degree in AI computation or system optimization with a strong computational profile, or equivalent experience and 3+ years of relevant work
  • Strong knowledge of C++, software development, programming techniques, and AI algorithms
  • Strong communication and organization skills, with a logical approach to problem solving, good time management, and task prioritization skills
  • Proficiency in a specific domain, such as multi-modal model training or post-training

What the JD emphasized

  • strong knowledge of C++, software development, programming techniques, and AI algorithms
  • Proficiency in a specific domain, such as multi-modal model training or post-training

Other signals

  • optimize AI workloads on GPUs
  • investigate and eliminate system bottlenecks
  • achieve best possible performance
  • research and develop innovative techniques in AI
  • comprehensive analysis and optimization