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Verkada is a cloud-managed physical security platform with over 30,000 customers including 100+ Fortune 500 companies. The company has a $5.8B valuation and more than $1 billion in annualized bookings, backed by CapitalG, Sequoia Capital, and other leading investors. With over 2 million devices deployed across 170+ countries, Verkada is at the forefront of physical AI technology.
The Streaming team owns the full-stack infrastructure powering the video experience for over 1.4 million Verkada cameras. This role focuses on designing and implementing streaming features that deliver live and recorded video with unmatched speed, reliability, and security.
As an Embedded Engineer specializing in Video Streaming, you will design, develop, and optimize embedded video encoding and streaming pipelines for Verkada's camera and security devices. Key responsibilities include implementing and tuning hardware-accelerated video codecs (H.264, H.265/HEVC, AV1) for performance, quality, and low power consumption. You'll build and extend multimedia frameworks such as GStreamer and FFmpeg to support real-time video capture, processing, and delivery. Integration and optimization of streaming protocols (RTSP, RTP, RTMP, HLS, DASH, WebRTC) for low-latency, reliable video transport at scale is essential. You'll profile and optimize startup time (TTFF), latency, rebuffering, and overall video quality of experience metrics. Debugging issues in encoding pipelines, transport layers, and device utilization (CPU/GPU/ISP) will be part of your daily work.
Required qualifications include a BS or MS degree in Computer Science or similar field, plus 5+ years of professional experience in embedded systems development with a focus on video streaming applications. Proficiency in C/C++ for embedded Linux environments is mandatory. The role requires full-time onsite presence five days per week in San Mateo.
Nice-to-have skills include strong hands-on experience with video codecs and hardware-accelerated encoding/decoding pipelines, familiarity with multimedia frameworks, solid understanding of video streaming protocols and adaptive bitrate streaming, and experience optimizing for low latency under constrained resources.
