Director of GPU-Accelerated Data Analytics

NVIDIA Corporation; Santa Clara (CA); Hybrid; USD 224,000 - 431,000; Full time

Benefits offered by this job

Equity

Benefits

Hybrid work

Job summary

NVIDIA Corporation seeks a visionary leader for its Developer Technology Engineering team to drive performance optimization across CPU/GPU workloads. You will guide a distributed team, collaborate with architects, and influence hardware/software roadmaps to unlock efficiency and savings in modern data centers.

Demonstrated leadership in high-performance computing, CUDA, and low-level optimization is required, along with strong communication skills and a track record of hiring top engineering

Qualifications

• MS or PhD in CS/CE or equivalent experience.
• 7+ years total with 4+ years in a technical role and 3+ years in engineering leadership.
• Outstanding leadership, cross-functional collaboration and project execution.
• Hands-on GPU/CUDA performance optimization experience.
• Fluency in C/C++, deep understanding of algorithms and software development.
• Deep CPU/GPU architecture fundamentals.
• Track record of building high-performing teams and hiring top engineers.
• Excellent communication and presentation skills.
• Ability to plan, lead and execute high-impact initiatives.

Responsibilities

• Lead a team of performance engineers collaborating with the developer community to optimize NVIDIA's CPUs/GPUs.
• Drive innovation by researching and developing techniques to optimize complex workloads across cloud and on-premise environments.
• Provide technical leadership by guiding software design decisions and architecture roadmaps.
• Grow and mentor a distributed team and foster a culture of collaboration and growth.

Skills

CUDA

C/C++

GPU parallel programming

Performance optimization

Leadership

Architectural knowledge

Education

MS/PhD in CS/CE

Equivalent experience

Job description

NVIDIA Corporation seeks a visionary leader for its Developer Technology Engineering team to drive performance optimization across CPU/GPU workloads. You will guide a distributed team, collaborate with architects, and influence hardware/software roadmaps to unlock efficiency and savings in modern data centers.

Demonstrated leadership in high-performance computing, CUDA, and low-level optimization is required, along with strong communication skills and a track record of hiring top engineering