C++ Software Engineer

About The Role We are seeking a C++ Software Engineer to develop and optimize software running on our edge devices for real-time video and audio processing. You will build high-performance pipelines for video ingestion, streaming, and analytics while ensuring low latency, concurrency, and reliability under constrained hardware environments. This role requires strong expertise in modern C++, multimedia frameworks, and networking protocols, with a focus on delivering production-grade edge computing solutions.

Responsibilities

• Design and develop high-performance C++ applications for video and audio processing.
• Implement real-time streaming pipelines using FFmpeg, GStreamer, and OpenCV.
• Work with network protocols (RTSP, RTP, HLS, WebRTC, TCP/UDP) to enable streaming and data exchange.
• Optimize software for latency, concurrency, and memory efficiency.
• Develop cross-platform applications targeting Linux and Windows environments.
• Debug and profile applications using Valgrind, GDB, perf, strace, and similar tools.
• Collaborate with AI engineers to integrate inference engines into the video pipeline.
• Ensure code quality through unit testing, code reviews, and documentation.
• Contribute to protocol design for communication between edge devices and servers.

Requirements

• 4+ years of experience in C++14/17/20/23 development.
• Deep knowledge of STL, Boost, and modern C++ concurrency primitives (std::thread, mutex, condition_variable, futures, async).
• Hands-on experience with FFmpeg, GStreamer, and OpenCV for video/audio capture, decoding, processing, and encoding.
• Strong understanding of RTSP, RTP, HLS, WebRTC, TCP/UDP networking.
• Experience with cross-platform development for Linux and Windows.
• Proficiency with tools like Valgrind, GDB, perf, strace.
• Familiarity with memory management, concurrency tuning, and real-time performance constraints.

Nice to Have

• Experience with AI inference engines (ONNX Runtime, TensorRT, OpenVINO) for real-time analytics.
• Knowledge of GPU programming (CUDA, OpenCL, Vulkan).
• Familiarity with containerized deployments (Docker, Kubernetes) for edge systems.
• Contributions to open-source multimedia or C++ libraries.
• Experience with low-level OS development (device drivers, kernel tuning).