NVIDIA is a world-leader in artificial intelligence and computer vision. Our team builds hardware-accelerated computer vision pipelines, cloud services and SDKs bringing the latest AI innovations to data centers, gaming rigs, cars, robots, buildings, medical devices, and more. We are looking for an engineering expert to help us productize and optimize the latest Vision Language Models (VLMs) and their pipelines. Together, we will democratize the use of these amazing models, unlocking all sorts of innovative applications the world is barely dreaming of.
What you'll be doing:
Develop, profile and optimize inference pipelines for VLMs and other AI CV models: improve throughput and latency, data loading, pre- and post-processing.
Improve the efficiency of VLM models themselves: kernel optimization in CUDA
Upstream improvements to SDKs and libraries across NVIDIA and beyond to deliver accelerated computer vision at scale.
Promote high-performance AI computer vision across NVIDIA teams and functions (Engineering, Product Management, Marketing, and more).
What we need to see:
Master's of Science in Computer Science or Electrical engineering or equivalent experience.
8 years practical experience or equivalent
Expertise in AI computer vision (VLMs, Vision Transformers, Diffusion models). Proven track record using its software ecosystem (PyTorch, HuggingFace, vLLM) to develop and release production-grade software.
Excellent software engineering fundamentals (source control, CI/CD, testing/validation, packaging, containerization, release).
Proficiency with Python, C++ and CUDA (kernel optimization)
Experience developing cloud applications (REST APIs, gRPC).
Excellent written, visual, and verbal communication to present performance challenges, tradeoffs, and architectural alternatives.
Curiosity and drive to learn new technologies and partner across teams and functions.
Ways to Stand Out from the Crowd:
Expertise in classical, non-ML computer vision
Strong fundamentals with system-level performance: multi-threaded, multi-process and distributed software development.
Grounding in mathematical fundamentals such as linear algebra, numerical methods, statistics, and exploratory data analysis.
History of creativity and innovation around performance in multiple problem domains.
You will also be eligible for equity and benefits.
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.
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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.”
