Would you enjoy researching new algorithms and discovering new techniques to optimize data intensive applications? Do you like investigating hardware and system bottlenecks, and optimizing the performance of critical applications on heterogeneous computing systems with CPUs and GPUs? Are you excited about the opportunity to work on the leading edge of technology with both visibility and impact to the success of a leader like NVIDIA? If so, the Developer Technology Team invites you to consider this opportunity.

The DevTech Engineer plays a crucial role in the success of NVIDIA and our customers. DevTechs work with external technologists to investigate performance of their applications, design parallel algorithms and implement optimizations in an accelerated computing environment. As recognized experts in the field we publish our findings in developer blogs or at relevant conferences and workshops. With insight to our customers, the industry, and academia we are important representatives of NVIDIA as a technology leader. Within NVIDIA we contribute valuable application expertise that influences next generation hardware and software products. As critical problem solvers, we deepen our expertise, expand our knowledge, and work across domains and organizations. Whether you are a leading industry luminary or early in your career, the DevTech Team provides ample opportunity for growth in the exciting field of accelerated computing!

• In this role, you will research and develop techniques to accelerate large scale applications running on NVIDIA's family of advanced GPU platforms.
• Work directly with other technical experts in their fields (industry and academia) to perform in-depth analysis and optimization of complex database and data analytics workloads to ensure the best possible performance on modern hardware architecture focused on GPU performance.
• Publish and present discovered optimization techniques in developer blogs or relevant conferences to engage and educate the Developer community.
• Influence the design of next-generation hardware architectures, software, and programming models in collaboration with research, hardware, system software, libraries, and tools teams at NVIDIA

• A Masters or PhD in Computer Science, Computer Engineering, or related computationally focused science degree (or equivalent experience).
• At least 3+ years of relevant work or research experience.
• Hands-on experience with low-level parallel programming and GPU programming, such as SIMD, multithreading, CUDA, or OpenCL.
• Knowledge of GPU architectures
• Programming fluency in modern C/C++ with a deep understanding of algorithms, concurrency, and other optimization techniques.
• Good communication and organization skills, with a logical approach to problem solving, and prioritization skills.