Software Engineer-Video Pipelines

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 .