Senior DevTech Engineer: GPU Performance & Optimization

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

Benefits offered by this job

Equity

Benefits package

Job summary

NVIDIA Corporation is seeking a Developer Technology Engineer (DevTech) to advance GPU-accelerated computing across CPUs, GPUs, and interconnects. You will collaborate with customers to optimize demanding workloads and work with cross-disciplinary teams to shape future programming models and architectures.

Ideal candidates have a Masters in CS/CE, 8+ years of relevant experience, strong C/C++, CUDA, and parallel programming skills, plus a track record in performance optimization and CPU/GPU

Qualifications

• Masters degree in CS, CE, or related field (or equivalent experience).
• 8+ years of relevant work experience or research.
• Proficiency in C/C++ with strong design, techniques, and algorithms.
• Background in parallel programming, ideally CUDA C/C++.
• Hands-on experience with low-level performance optimizations.
• Deep expertise in CPU/GPU architecture fundamentals.
• Strong math skills, including linear algebra.
• Excellent communication and prioritization skills.

Responsibilities

• Research and develop techniques to accelerate CSP workloads on NVIDIA's computing platform including CPUs, GPUs and interconnects.
• Work directly with key customers to analyze and optimize complex workloads for best performance on current and next-gen hardware.
• Collaborate with libraries, tools, system software architecture, hardware, and research teams to influence next-gen programming models, software and architectures.

Education

Masters in Computer Science / Computer Engineering or related field

8+ years of relevant work experience or research

C/C++ proficiency

CUDA C/C++ background

Parallel programming

CPU/GPU architecture fundamentals

Mathematics / Linear algebra

Communication and organizational skills

Job description

NVIDIA Corporation is seeking a Developer Technology Engineer (DevTech) to advance GPU-accelerated computing across CPUs, GPUs, and interconnects. You will collaborate with customers to optimize demanding workloads and work with cross-disciplinary teams to shape future programming models and architectures.

Ideal candidates have a Masters in CS/CE, 8+ years of relevant experience, strong C/C++, CUDA, and parallel programming skills, plus a track record in performance optimization and CPU/GPU