NVIDIA
NVIDIA
NVIDIA o‘yinlar, ma’lumotlar markazlari, bulutli hisoblash, sog‘liqni saqlash, ishlab chiqarish, avtomobilsozlik va robototexnika sohalarida qo‘llaniladigan tezlashtirilgan hisoblash hamda sun’iy intellekt texnologiyalarini ishlab chiqadi. Kompaniyaning faoliyati grafik protsessorlar, sun’iy intellekt platformalari, simulyatsiya va muayyan sohalarga mo‘ljallangan yechimlarni qamrab oladi. Bular qatoriga hamkorlikdagi 3D ish jarayonlari uchun NVIDIA Omniverse, avtonom transport vositalarini ishlab chiqish uchun NVIDIA DRIVE va sog‘liqni saqlash ilovalari uchun NVIDIA Clara kiradi. Kompaniya ilg‘or hisoblash, simulyatsiya va sun’iy intellekt asosidagi tahlilni qo‘llab-quvvatlaydigan infratuzilma hamda dasturiy ta’minot ustida ishlaydigan yirik texnik jamoalarni birlashtiradi.

Senior Video System Software Engineer at NVIDIA, Bengaluru Onsite

Senior engineer building GPU-accelerated video streaming software for NVIDIA GeForce NOW cloud gaming, with a focus on codecs, video quality, reliability, AI processing, and latency.

Tavsif

  • Create video streaming capabilities that enable new interactive experiences
  • Build features that improve image quality, performance, reliability, security, and maintainability
  • Profile GPU and CPU performance across the video pipeline, identify bottlenecks, and implement solutions with GPU hardware and software teams
  • Develop tools to measure video quality from the user’s perspective and assess improvements
  • Use modern video compression technologies to deliver high-quality streaming for interactive graphics applications
  • Build quality assessment and analysis tools using video metrics and encoder statistics to identify regressions, assess features, and guide codec and pipeline tuning
  • Apply machine learning and AI models to video processing and adaptive streaming algorithms that reduce artifacts and latency across changing network conditions

Talablar

  • At least five years of experience and a bachelor’s or master’s degree in computer science or a related field
  • Proficiency in C, C++, and Python
  • Strong knowledge of real-time, GPU-accelerated video pipeline performance, including encoder behavior, color spaces, scaling, transport efficiency, buffering, pacing, bitrate adaptation, frame handling, and latency optimization in distributed or cloud systems
  • Familiarity with Vulkan, CUDA, OpenGL, and DirectX APIs
  • Strong understanding of H.264, HEVC, and AV1 codecs, including configuration tuning and application trade-offs
  • Experience debugging and improving reliability in complex streaming systems under degraded network conditions, including packet-loss recovery, telemetry, tracing, field validation, and long-running sessions
  • Proficiency in telemetry, statistical analysis, and performance monitoring for cloud infrastructure
  • Experience integrating AI models into real-time video pipelines
  • Experience with objective video quality assessment using VMAF, CAMBI, PSNR, and SSIM/MS-SSIM, including correlation with perceived quality
  • Strong understanding of operating-system internals, user-mode and kernel-mode drivers, system software performance analysis, testing, and debugging
  • Experience optimizing video pipelines across GPU families such as Intel integrated graphics and AMD GPUs
  • Experience developing or analyzing graphics-rendering applications or advanced AI-based graphics-generation technologies such as DLSS, RTX, or FSR

Imtiyozlar

  • NVIDIA is an equal opportunity employer committed to diversity, equity, and inclusion

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