We are seeking an AI Developer Technology (DevTech) Engineer to accelerate the frontier of generative AI training and inference. Our team is the bridge connecting the NVIDIA platform with developers worldwide. We dive deep into customer projects to accelerate performance, eliminate bottlenecks, and partner with a vibrant developer community to deliver outstanding performance on NVIDIA systems.
If you are passionate about accelerating the world's most advanced AI models and want your insights to directly influence the future of NVIDIA hardware and software stacks, we want you to be on our team.
What you will be doing:
- Develop cutting-edge techniques to GPU-accelerate complex workloads across state-of-the-art generative AI (including LLMs, diffusion models, and multimodal systems), deep learning, and machine learning domains.
- Work directly with key developers to optimize and accelerate generative AI training and inference on NVIDIA platform. Build and optimize algorithms to deliver the best performance, and contribute to training and inference frameworks, low-level software libraries, and open-source projects.
- Partner directly with top technical experts in industry and academia to perform in-depth analysis and optimization of complex AI algorithms on modern CPU and GPU architectures.
- Shape the design of next-generation hardware, system software, libraries, and programming models through tight collaboration with NVIDIA’s internal engineering and research teams.
- Share your breakthrough optimization techniques by publishing in developer blogs and presenting at industry conferences.
What we need to see:
- MS in Computer Science, Computer Engineering, or related computational field (or equivalent experience)
- 1+ years of relevant work or research experience in software engineering and performance tuning.
- Programming fluency in C/C++ with a deep understanding of algorithms and software development.
- A background in accelerated computing, with comprehensive knowledge of parallel programming, performance analysis and optimization.
- Hands on experience doing low-level performance optimizations.
- Foundational understanding of modern CPU and GPU architectures.
- Good communication and organization skills, with a logical approach to problem solving, and prioritization skills.
Ways to stand out from the crowd:
- PhD in a relevant field.
- Experience with training and inference stacks, serving frameworks, pre-training and post-training pipelines.
- Strong foundation in linear algebra and numerical methods.
What's DevTech? We are a global organization whose mission is to drive innovation we see in the market towards our products. As recognized specialists across many domains, our work makes valuable contributions in two important ways. Our solutions are at the cutting edge of technology, advancing NVIDIA’s leadership in accelerated computing. Our discoveries generate findings that benefit the Developer Community and provides guidance to our engineering teams to help make our products better. NVIDIA's success in the advancement and availability of Artificial Intelligence has created incredible growth across the Company, and our Developer Technology Engineering team has been steadily growing to meet the demands for our services.
#LI-Hybrid
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD for Level 2, and 152,000 USD - 241,500 USD for Level 3.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Skills Required
- MS in Computer Science, Computer Engineering, or a related computational field, or equivalent experience
- At least 1 year of relevant software engineering or performance tuning work or research experience
- Programming fluency in C/C++
- Deep understanding of algorithms and software development
- Background in accelerated computing
- Comprehensive knowledge of parallel programming, performance analysis, and optimization
- Hands-on experience with low-level performance optimization
- Foundational understanding of modern CPU and GPU architectures
- Good communication and organization skills
- Logical problem-solving and prioritization skills
- PhD in a relevant field
- Experience with training and inference stacks, serving frameworks, and pre-training and post-training pipelines
- Strong foundation in linear algebra and numerical methods
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
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