Senior System Software Engineer, Computer Vision Performance

at Nvidia

📍 Santa Clara, United States

$220,000-419,800 per year

SENIOR
✅ Hybrid

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Software Development @ 7 Kubernetes @ 4 Python @ 4 Statistics @ 4 CI/CD @ 4 Algorithms @ 4 MLOps @ 7 Leadership @ 4 Communication @ 4 Microservices @ 4 Data Analysis @ 4 Technical Leadership @ 4

Details

NVIDIA is a world-leader in high speed computer vision, artificial intelligence, and deep learning. Our team builds and optimizes computer vision AI models, SDKs, and cloud services to bring real-time hardware-accelerated AI to data centers, gaming rigs, cars, robots, buildings, medical devices, and more.

Responsibilities

  • Profile, debug, and optimize data-center and edge computer vision workloads for efficiency, latency, and throughput.
  • Implement and improve computer vision and image processing algorithms using CUDA.
  • Establish and drive product-critical performance metrics.
  • Influence software architecture and technical roadmaps to ensure outstanding performance.
  • Contribute to large codebases combining custom C++ and Python with distributed architectures (microservices, Kubernetes, Triton) to deliver computer vision at scale.
  • Provide technical leadership in high-performance computing to computer vision teams across NVIDIA.

Requirements

  • Master's of Science in Computer Science or Electrical engineering (or equivalent experience).
  • 10+ years 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 C++, CUDA, and Python.
  • Strong fundamentals with multi-threaded and distributed software development.
  • Experience with performance-critical data center applications.
  • Proven track record defining and driving performance metrics to ensure product success and differentiation.
  • Excellent written, visual, and verbal communication to present performance challenges, tradeoffs, and architectural alternatives.
  • Strong collaboration skills to partner with algorithm designers, application developers, and infrastructure and MLOps teams.
  • Ability and desire to learn new technologies.

Ways to Stand Out from the Crowd

  • Experience with classical and machine-learning based computer vision including ML-Ops.
  • 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.