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# Senior Systems Software Engineer - QoS

- **Company:** NVIDIA Ltd.
- **Location:** Santa Clara, CA, United States
- **Experience:** Expert
- **Salary:** $152,000.0 - $287,500.0
- **Contract:** Permanent contract
- **Skills:** Microsoft Windows, Cloud Computing, Encodings, Data Visualization, Software Debugging, Linux, Datagram Transport Layer Security, Embedded Operating Systems, H.264/MPEG-4 AVC, Socket Programming, Software Engineering, Video Codec, Video Encoding, WebRTC, Multithreading, High Efficiency Video Coding (HEVC), Information Technology, Low Latency, Data Analytics, Transport Protocols, Automotive Software, Decoding, Stream Control Transmission Protocol
- **Published:** July 24, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=ba2c2f6e590d0dbb

## About the Role

* Master degree in Computer Science or Electrical Engineering (or equivalent experience)
 * 5+ years of proven experience in C++ software development, optimization, test and debugging skills.
 * Deep knowledge of operating systems, multi-threading, socket programming, and performance-critical programming in Windows and Linux.
 * Good understanding of some of low-latency transport protocols (e.g., WebRTC, QUIC)
 * Strong analytical and problem-solving skills, with a self-motivated approach.

Ways to stand out from the crowd:

 * In-depth knowledge of WebRTC architecture, peer connection lifecycle, ICE handshake, and real-time protocols (SRTP, DTLS-SRTP, SCTP).
 * Knowledge of video codecs including H.264, H.265, AV1, color spaces, or hardware-accelerated encode/decode.
 * Experience with automotive software, telematics, connected vehicle platforms, infotainment, or car connectivity.
 * Experience with QNX, QNX Safety, Linux, or embedded operating systems for safety-critical platforms is a strong plus.
 * Proficiency in using analytics and visualization tools for data-driven software development

## Description

* Design, develop and test high-performance C++ software for ultra low-latency streaming
 * Build and improve media streaming pipelines using technologies such as WebRTC, GStreamer, RTP/RTCP, and related protocols.
 * Analyze performance metrics across server, network and media pipeline and optimize GPU and CPU utilization to reduce latency.
 * Define and implement KPIs for streaming quality, and user experience.
 * Collaborate with video encoding, cloud networking, and systems teams to deliver low-latency, high-fidelity streaming experience


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