Senior AI DevTech Engineer: GPU-Accelerated LLMs

NVIDIA Corporation; Santa Clara (CA); On-site; USD 184,000 - 357,000; Full time

Job summary

NVIDIA in Santa Clara, CA seeks a Senior AI Developer Technology Engineer to accelerate generative AI training and inference on NVIDIA platforms. You will optimize algorithms, contribute to libraries, and collaborate with industry experts, shaping future hardware/software stacks.

The role emphasizes deep performance analysis, parallel programming, and low‑level optimizations, with opportunities to publish findings and present at conferences.

Qualifications

• MS in computer science, computer engineering, or related field or equivalent experience.
• 8+ years of software engineering and performance tuning experience.
• Fluency in C/C++ with strong algorithms background.
• Background in accelerated computing, parallel programming, performance analysis and optimization.
• Hands‑on experience with low‑level performance optimizations.
• Foundational understanding of modern CPU and GPU architectures.
• Strong communication and organizational skills.

Responsibilities

• Develop GPU-accelerated techniques for generative AI workloads (LLMs, diffusion, multimodal).
• Collaborate with developers to optimize training and inference on NVIDIA platforms.
• Contribute to training/inference frameworks, libraries, and open‑source projects.
• Analyze and optimize complex AI algorithms on CPU/GPU architectures with internal teams.
• Publish breakthrough techniques in developer blogs and at conferences.

Skills

C/C++

Parallel programming

Performance tuning

Low‑level optimizations

CPU/GPU architectures

Communication skills

Education

MS in CS/CE

Job description

NVIDIA in Santa Clara, CA seeks a Senior AI Developer Technology Engineer to accelerate generative AI training and inference on NVIDIA platforms. You will optimize algorithms, contribute to libraries, and collaborate with industry experts, shaping future hardware/software stacks.

The role emphasizes deep performance analysis, parallel programming, and low‑level optimizations, with opportunities to publish findings and present at conferences.