Join NVIDIA's GeForce NOW team, a revolutionary cloud-based gaming service, and help shape the future of gaming. We're expanding our cutting-edge technology to encompass virtual and augmented reality, AI, and remote robotics.

This role focuses on developing a high-performance, low-latency streaming stack to deliver unparalleled video quality, making cloud gaming the preferred platform for millions worldwide.

Innovate and design new video streaming features for immersive interactive experiences. Improve image quality, performance, reliability, security, and maintainability. Analyze and optimize GPU/CPU performance within the video pipeline, collaborating with hardware and software teams. Develop sophisticated tools to measure user-perceived video quality and enable confident evaluation of improvements. Leverage advanced video compression technologies to craft high-quality streaming solutions for diverse interactive graphics applications. Build quality evaluation and analysis capabilities using metrics and encoder statistics to identify regressions, assess new features, and guide pipeline tuning. Apply machine learning and AI models for specialized video processing and adaptive streaming, minimizing artifacts and latency across various network conditions.

A Bachelor's or Master's degree in Computer Science or a related field, with over 5 years of experience.

Required skills include proficiency in C, C++, and Python, alongside a deep understanding of real-time GPU-accelerated video pipelines. This encompasses encoder behavior, color spaces, video scaling, transport efficiency, buffering, pacing, bitrate adaptation, frame handling, and latency-sensitive optimizations in distributed or cloud environments.

Familiarity with API frameworks like Vulkan, CUDA, OpenGL, and DX is essential. A strong grasp of video codecs such as H.264, HEVC, and AV1, including their tuning, is crucial. Experience in debugging and enhancing the reliability of complex streaming systems, especially under degraded network conditions, is vital. Proficiency in telemetry, statistical data analysis, and performance monitoring is also key.

Experience integrating AI models into real-time video pipelines and conducting objective video quality assessments using metrics like VMAF, CAMBI, PSNR, and SSIM/MS-SSIM is highly valued. A solid understanding of software stack layers, OS internals, and system software performance analysis, testing, and debugging skills are required.