Embedded Video Systems Engineer - Surgical Training Platform

Company Description MYL Instruments is developing SYLVIE, a surgical AI Co-Pilot designed to improve operating room efficiency and support surgical teams. SYLVIE learns real surgical workflows and individual surgeon preferences to provide intelligent, context-aware assistance. By optimizing OR productivity, reducing surgical supply waste, and streamlining staff onboarding, MYL Instruments helps hospitals operate more effectively. The company's mission is to make world-class OR efficiency accessible to hospitals of all sizes, using advanced AI and edge technologies. Role Description You will own the end-to-end development of an edge video system deployed in and around operating rooms. The system captures first-person video from multiple wired head-mounted cameras and an SDI source, records simultaneous encrypted streams on an embedded AI computer, displays a selected feed over HDMI with physical-button controls, and securely uploads recordings and communicates to our backend server after each session. This is a hands-on, high-ownership role spanning embedded Linux, real-time video pipelines, camera and capture-card integration, security implementation, and hardware work, from architecture and prototyping through verification, documentation, and pilot handover. What You'll Do Architect and implement a multi-stream video pipeline on edge devices: simultaneous ingest of networked camera streams and SDI feed, multiple-feed independent recording, and low-latency HDMI display of a selected feed with digital zoom and pan/crop. Build the capture nodes: camera integration (V4L2 / vendor SDKs), hardware-accelerated encoding, and reliable low-latency streaming over a dedicated wired network, fully offline. Evaluate and integrate candidate head-mounted cameras and SDI capture hardware; produce compatibility assessments covering interfaces, drivers, latency, and integration risk. Implement the security baseline. Deliver a fully headless system: automatic startup and recovery, physical start/stop, feed-selection, zoom, and directional controls via GPIO, and status LEDs. Integrate remote administration and telemetry: Systems Manager enrollment, application telemetry to backend endpoints, remote software/container/model deployment and rollback support. Ensure the video services preserve GPU and compute headroom for MYL's on-device AI processing pipeline running on the same platform. Conduct verification testing (8-hour continuous recording, interruption recovery, concurrency, latency) and produce complete documentation, deployment materials, and a reproducible-build handover package. Minimum Qualifications 3+ years of professional experience in embedded systems, video/streaming engineering, or edge computing on Linux. Strong proficiency with embedded Linux: systemd services, udev, headless operation, automatic startup and recovery, Bash scripting. Hands-on experience building video pipelines with GStreamer, FFmpeg, or NVIDIA DeepStream, including multi-stream ingest (RTSP/RTP), hardware-accelerated H.264/H.265 encoding, and simultaneous recording. Direct experience with NVIDIA Jetson platforms (JetPack, NVENC/NVDEC, multimedia API) or closely equivalent embedded GPU/SoC video work. Camera integration experience: V4L2, USB/IP camera SDKs, and driver-level troubleshooting. Solid networking fundamentals: wired network design, streaming protocols, connection monitoring, and automatic reconnection handling. Working knowledge of AWS service integration from device software: REST APIs, S3 multipart uploads with presigned URLs, and retry/resume logic. Practical security implementation skills: TLS/mTLS, certificate management, and disk or file-level encryption on Linux. Strong C/C++ and/or Python; Git; Docker or containerized deployment. Basic embedded hardware skills: GPIO for buttons and LEDs, debouncing, and simple wiring on developer-kit hardware. Ability to work independently through a phased development plan, document thoroughly, and communicate technical risk early and clearly. Preferred Qualifications Experience with TPM 2.0 provisioning and hardware-backed key storage. Experience with AWS Systems Manager (SSM) managed-node enrollment and remote fleet administration. SDI capture-card integration (Blackmagic DeckLink, Magewell, AJA). TensorRT or DeepStream deployment experience, or familiarity with resource budgeting for on-device ML workloads. Prior work in medical devices, operating rooms, or other regulated, privacy-sensitive environments. Experience writing formal verification test reports and structured handover/documentation packages. Bilingual (English/French) an asset.

You will own the end-to-end development of an edge video system for surgical training. This includes architecting a multi-stream video pipeline, building capture nodes, and ensuring system security and reliability.

Candidates should have 3+ years of experience in embedded systems and video engineering, with strong proficiency in embedded Linux and video pipeline development. Familiarity with NVIDIA Jetson platforms and camera integration is also required.

Identified from the job description. Confirm important requirements above.

• Embedded Systems
• Video Engineering
• Edge Computing
• Embedded Linux
• GStreamer
• FFmpeg
• NVIDIA Jetson
• Camera Integration
• Networking
• AWS Integration
• Security Implementation
• C/C++
• Python
• Docker
• GPIO
• TLS

Minimum experience

5+ years

Apply by

Jan 8, 2027