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Verkada is a cloud-managed physical security platform with over 30,000 customers (including 100+ Fortune 500 companies), a $5.8B valuation, and more than $1 billion in annualized bookings. The company powers video security, access control, air quality sensors, alarms, intercoms, and visitor management through an integrated, AI-powered platform deployed across 170+ countries.
The Streaming team owns the full-stack infrastructure powering the video experience for over 1.4M Verkada cameras. As an Embedded Engineer focused on Video Streaming, you will design and implement streaming features that power the company's deployed cameras and next-generation devices. You'll collaborate with firmware, backend, and native client teams to build and own a highly performant streaming capture experience for both live and historical video playback.
Key responsibilities include:
- Design, develop, and optimize embedded video encoding and streaming pipelines for Verkada's camera and security devices
- Implement and tune hardware-accelerated video codecs (H.264, H.265/HEVC, AV1) for performance, quality, and low power consumption
- Build and extend multimedia frameworks (e.g., GStreamer, FFmpeg) to support real-time video capture, processing, and delivery
- Integrate and optimize streaming protocols (RTSP, RTP, RTMP, HLS, DASH, WebRTC) for low-latency, reliable video transport at scale
- Profile and optimize startup time (TTFF), latency, rebuffering, and overall video quality of experience metrics
- Debug issues in encoding pipelines, transport layers, and device utilization (CPU/GPU/ISP)
Required qualifications:
- BS or MS degree in Computer Science or similar
- 5+ years of professional experience in embedded systems development with focus on video streaming applications
- Proficiency in C/C++ for embedded Linux environments
- Must be willing and able to work onsite five days per week
Desirable experience includes strong hands-on work with video codecs and hardware-accelerated encoding/decoding pipelines, familiarity with multimedia frameworks like GStreamer or FFmpeg, solid understanding of video streaming protocols and adaptive bitrate streaming, and experience optimizing for low latency under constrained resources.
