Developer Technology Engineer – LLM

About NVIDIA

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

What You'll Be Doing as a Developer Technology Engineer – LLM

• Study and develop cutting-edge techniques in deep learning, graphs, machine learning, and data analytics, and perform in-depth analysis and optimization to ensure the best possible performance on current- and next-generation GPU architectures.
• Working on key applications (e.g., LLM training and inference) to understand the current and future problems they are solving, crafting and optimizing core parallel algorithms and data structures to provide the best solutions using GPUs, through both library development and direct contribution to the applications.
• Collaborating closely with diverse groups at NVIDIA such as the architecture, research, libraries, tools, and system software teams to influence the design of next-generation architectures, software platforms, and programming models, by investigating the impact on application performance and developer efficiency.
• Travel for on-site visits with developers and to conferences.

What We Need To See

• MS or PhD from a leading University in an engineering or Computer Science related field.
• 3+ years working experience.
• Strong and practical knowledge of programming techniques, and AI algorithms.
• Experience in large-scale language model (LLM) training or inference, including the development of LLM frameworks and performance optimization.
• Experience with parallel programming, ideally CUDA C/C++.
• Excellent communication and organization skills, with a logical approach to problem solving, good time management and task prioritization.

Key skills/competency

• Deep Learning
• Machine Learning
• LLM Training
• LLM Inference
• GPU Optimization
• CUDA C++
• Parallel Programming
• AI Algorithms
• Data Structures
• Software Development