Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Algorithms @ 4
Data Structures @ 4
Hiring @ 4
Communication @ 4
Parallel Programming @ 4
Prioritization @ 4
CUDA @ 4
GPU @ 4
AI @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA's Developer Technology Engineering team is a global network of experts working on accelerating industry workloads using advanced CPUs, GPUs and interconnects. The team helps developers optimize large application workloads, remove system bottlenecks, and collaborate on next-generation software and hardware design.
Responsibilities
- Research and develop techniques to accelerate top CSP workloads on NVIDIA’s computing platform including advanced CPUs, GPUs and interconnects.
- Work directly with key customers to perform in-depth analysis and optimization of complex workloads to ensure best possible performance on current and next-generation hardware.
- Collaborate with libraries, tools, system software architecture, hardware, and research teams at NVIDIA to influence the design of next-generation programming models, software, and architectures.
- Investigate application performance, design parallel algorithms, and implement optimizations in GPU-accelerated computing environments.
- Publish findings in developer blogs or at conferences and represent NVIDIA to customers, industry, and academia.
Requirements
- Master's degree in Computer Science, Computer Engineering, or related computationally focused science degree (or equivalent experience).
- 8+ years of relevant work experience or research.
- Programming proficiency in C/C++ with a deep understanding of software design, programming techniques, and algorithms.
- Background in parallel programming, ideally CUDA C/C++.
- Hands-on experience performing low-level performance optimizations.
- In-depth expertise with CPU and GPU architecture fundamentals.
- Strong math skills, including linear algebra, for problem-solving and performance modeling.
- Good communication, organization, and prioritization skills.
Ways to stand out
- Designed highly optimal parallel algorithms and data structures for applications with high bytes-to-compute ratio (e.g., processing directly on compressed data and kernel fusion).
- Optimized end-to-end performance of applications spanning many layers of software, from OS to high-level frameworks.
- Influenced hardware feature design leveraging application and domain knowledge.
Compensation and Benefits
- Base salary ranges (location and level dependent):
- Level 4: 184,000 USD - 287,500 USD
- Level 5: 224,000 USD - 356,500 USD
- Eligible for equity and company benefits (link referenced in original posting).
Additional information
- Work arrangement: Hybrid (#LI-Hybrid).
- Application deadline: Applications accepted at least until March 20, 2026.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer and values diversity in hiring and promotion practices.