Senior Software Engineer, Metropolis Vision AI

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

Senior Software Engineer role focused on building and optimizing large-scale, distributed Vision AI platforms and pipelines for real-time and streaming scenarios. The role involves developing multi-modal perception capabilities, using simulation and synthetic data, and profiling/tuning GPU-accelerated inference. It requires strong C++/Python, computer vision, deep learning, and production deployment experience.

What you'd actually do

  1. Crafting and implementing high-performance Vision AI pipelines for real-time and streaming scenarios using brand-new computer vision and deep learning models.
  2. Developing and refining large-scale distributed services responsible for processing video, image, and 3D data in both edge and cloud settings.
  3. Developing multi-modal perception capabilities that combine 2D, 3D, and temporal information to understand complex real-world scenes.
  4. Using simulation and synthetic data tools to build, test, and validate perception algorithms at scale.
  5. Profiling and tuning GPU-accelerated inference pipelines to meet strict latency, efficiency, and reliability targets.

Skills

Required

  • BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, or a related field, or equivalent experience.
  • 12+ years of professional software development experience using modern C++ (14/17/20) and Python on Linux.
  • Strong computer science fundamentals, including algorithms, data structures, concurrency, and distributed systems concepts.
  • Demonstrated expertise in computer vision and deep learning, with a history of deploying production systems in these fields.
  • Experience building and debugging high-performance, concurrent systems, including multi-threading, asynchronous I/O, and efficient memory management.
  • Proficiency working in Linux-based environments with containers and microservices, integrating AI components into scalable back-end services.
  • Ability to rapidly prototype vision models and pipelines, then evolve them into production-quality services.
  • Practical experience with PyTorch in training, fine-tuning, and deploying models for vision tasks.
  • Strong analytical and problem-solving skills, with a data-driven approach to performance optimization and system build.
  • Excellent written and verbal communication skills, with demonstrated success collaborating across time zones and functions.

Nice to have

  • Proven experience delivering end-to-end computer vision applications in production, such as video analytics, smart cities, autonomous systems, retail analytics, industrial inspection, or digital twins.
  • Practical experience with GPU acceleration (such as CUDA, TensorRT, or comparable technologies) and low-level optimization for inference and pre/post-processing.
  • Experience in simulation and synthetic data creation employing tools such as Omniverse, Unreal Engine, Unity, or similar digital-twin platforms.
  • Background in vision-language models or related multi-modal AI, including integrating these models into real products.
  • Background in multimedia, including video-centric processing and delivery (such as codecs, video pipelines, or media frameworks) and integrating vision models into multimedia workflows.

What the JD emphasized

  • deploying production systems
  • high-performance
  • large-scale distributed
  • GPU-accelerated inference pipelines
  • real-time
  • streaming scenarios
  • multi-modal perception capabilities
  • simulation and synthetic data tools
  • production-quality services
  • end-to-end computer vision applications in production

Other signals

  • large-scale distributed services
  • high-performance Vision AI pipelines
  • GPU-accelerated inference pipelines
  • deploying production systems