Role Overview
We are looking for a Software Engineer – Video Pipelines to join our Video AI Platform team. This role is focused on building robust, high-performance video pipelines for both Video-on-Demand (VoD) and Live streaming systems . You will be hands-on in implementing modules for video decoding, encoding, transcoding, and modification , ensuring that our platform delivers low-latency, high-quality video experiences at scale.
As a pipeline-builder, you will work closely with senior engineers and architects to bring designs and AI workflows into production-ready video systems , using frameworks like FFmpeg, GStreamer, and GPU-accelerated SDKs .
Key Responsibilities
Video Pipeline Engineering
- Build and maintain video ingestion, decoding, encoding, and transcoding pipelines for VoD and Live systems.
- Integrate adaptive bitrate streaming (HLS, DASH) into delivery pipelines.
- Work with FFmpeg, GStreamer, NVIDIA Video Codec SDK, and VAAPI to implement efficient video processing components.
- Ensure pipeline compatibility with multiple codecs and containers (H.264/H.265, AV1, VP9, MP4, MKV, TS).
Video Modification Modules
- Implement frame-accurate transformations such as redaction (face/voice blurring), reframing, auto-zoom, and overlays.
- Build timeline-aware components that align scene metadata with video streams for precise modifications.
- Optimize GPU-accelerated filters for real-time and batch processing .
Performance & Scalability
- Profile and tune pipelines for low-latency live streaming and high-throughput VoD workflows .
- Contribute to scaling strategies for large video libraries and live event workloads.
- Optimize for cloud cost efficiency while maintaining reliability.
Collaboration & Execution
- Work with senior engineers to translate designs into production components .
- Collaborate with AI teams to integrate model outputs into video pipelines (e.g., scene tagging, redaction cues).
Participate in code reviews, testing, and deployment automation .
Qualifications
Must-Have
- 2–5 years of experience in video pipeline or multimedia systems engineering .
- Strong coding skills in C++ and/or Python .
- Hands-on experience with FFmpeg, GStreamer, libx264/x265, NVENC/DEC .
- Understanding of video codecs and streaming protocols (H.264/H.265, VP9, AV1, HLS, DASH, RTMP).
- Familiarity with GPU acceleration (CUDA, NVENC/DEC, VAAPI, or equivalent).
Nice-to-Have
- Exposure to cloud-native deployments (AWS/GCP/Azure, Docker, Kubernetes).
- Experience in real-time video editing or transformation pipelines .
- Familiarity with timeline-based metadata, content retrieval, or AI-driven video modifications .
- Knowledge of adaptive streaming and edge delivery optimizations .