Senior System Software Engineer

NVIDIA NVIDIA · Semiconductors · Pune, India +2

Senior Software Engineer for NVIDIA's GeForce NOW, focusing on developing and optimizing a high-performance, low-latency video streaming stack. The role involves designing new video streaming functionalities, improving image quality and performance, analyzing GPU/CPU performance, and applying ML/AI models for specialized video processing and adaptive streaming algorithms. Experience with real-time video pipelines, GPU acceleration, video codecs, telemetry, and AI model integration is required.

What you'd actually do

  1. Design and develop new video streaming functionalities delivering new interactive experiences
  2. Innovate, design and develop features to improve image quality, performance, reliability, security and maintainability
  3. Analyze GPU/ CPU performance for the video pipeline, isolate bottlenecks and implement solutions in collaboration with GPU hardware and software teams to deliver top performance
  4. Develop tools to measure video quality experienced by users, refine to enable evaluation of quality improvements with high confidence
  5. Leverage features and toolsets in latest video compression technologies to deliver high quality streaming solutions tailored for different interactive graphics applications

Skills

Required

  • 5 + years of experience with Bachelor's or Master's degree in Computer Science or a related area.
  • Proficiency in C, C++, Python
  • Strong understanding of real-time GPU-accelerated video pipeline performance, including encoder behavior, color spaces, video scaling, transport efficiency, buffering, pacing, bitrate adaptation, frame handling, and latency-sensitive optimizations in distributed or cloud-based systems.
  • Familiarity with API frameworks such as Vulkan, CUDA, OpenGL and DX
  • Solid understanding of toolsets in different video codecs like H.264, HEVC, and AV1, including tuning codec configurations to meet application requirements and trade-offs.
  • Experience debugging and improving reliability and stability in complex streaming systems, including issues related to degraded network conditions, packet loss recovery, telemetry, tracing, field validation, and long-running session behavior.
  • Proficiency in telemetry, statistical data analysis, and performance monitoring to measure and optimize video quality, latency, and system performance in cloud infrastructures.
  • Experience in using and integrating AI models into real-time video pipelines
  • Experience with objective video quality assessment using metrics such as VMAF, CAMBI, PSNR, and SSIM/MS-SSIM, and the ability to correlate those metrics with perceptual video quality across different content types and artifacts.
  • Strong understanding of different layers of software stack including OS internals, user-mode and kernel-mode drivers, strong system software performance analysis, testing and debugging skills

Nice to have

  • Experience in optimizing video pipelines on multiple GPU families such as Intel integrated and AMD GPUs
  • Experience writing or analyzing graphics rendering applications or advanced AI based graphics generation such as DLSS, RTX, FSR

What the JD emphasized

  • real-time GPU-accelerated video pipeline performance
  • latency-sensitive optimizations
  • AI models into real-time video pipelines
  • objective video quality assessment

Other signals

  • Develop quality-evaluation and analysis capabilities that use metrics along with encoder statistics to detect regressions, evaluate new video features, and guide codec and pipeline tuning.
  • Apply machine learning and AI models to develop specialized video processing and adaptive streaming algorithms to minimize perceptible artifacts while delivering the lowest latency under different network conditions.
  • Experience in using and integrating AI models into real-time video pipelines