Nvidia-posted 4 months ago
$184,000 - $287,500/Yr
Full-time • Senior
Remote • Santa Clara, CA
Computer and Electronic Product Manufacturing

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 expert in system-level software optimization to push our computer vision applications to near speed of light. The right candidate will bring insight into challenges of delivering performance at scale and passion for multi-disciplinary teamwork and efficient, well-crafted software.

  • Develop, profile and optimize data-center and edge computer vision workloads for efficiency, latency, and throughput (Python).
  • Implement and improve computer vision and image processing algorithms using CUDA.
  • Upstream performance improvements to SDKs and libraries across NVIDIA to deliver accelerated computer vision at scale.
  • Influence software architecture, validation strategy and technical roadmaps to ensure outstanding performance.
  • Promote high-performance computer vision across NVIDIA teams and functions (Engineering, Product Management, Marketing, and more).
  • Master's of Science in Computer Science or Electrical engineering or equivalent experience.
  • 8 years of practical experience.
  • Excellent software engineering fundamentals (source control, CI/CD, testing/validation, packaging, containerization, release).
  • Proven track record developing, testing and releasing production-grade, complex software.
  • Proficiency with Python, CUDA and C++.
  • Strong fundamentals with multi-threaded, multi-process and distributed software development.
  • Expertise defining and driving performance metrics through profiling and benchmarking.
  • Experience developing performance-critical data center and 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.
  • Expertise in classical, non-ML computer vision.
  • Expertise in ML computer vision (VLMs, Vision Transformers, Diffusion models) and its software ecosystem: PyTorch, HuggingFace, vLLM.
  • 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.
  • Equity and benefits.
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