R&D Lead Engineer

At CraftifAI, were building CraftifAI Orbit a GenAI-native workflow platform that automates embedded, edge AI, and IoT software development. Orbit is an intelligent engineering orchestration system that streamlines how device software is created, validated, optimized, flashed, and deployed across heterogeneous hardware.

We need a Lead R&D Engineer who can build high-throughput real-time video pipelines, de-risk deployment on physical devices, debug accuracy/performance at the deepest engineering levels, and lead the architectural partitioning of applications across heterogeneous edge systems.

• Build the core engine of CraftifAI Orbit workflow automation, pipeline composition, deployment, debugging, benchmarking, and hardware abstraction.
• Design + implement real-time embedded video pipelines using GStreamer, V4L2, V4L2-loopback, and camera/media subsystems on Linux.
• Lead edge deployment validation across RTSP, WebRTC, H.264 encoders, Ethernet, USB, PCIe, and MIPI interfaces.
• Partition applications across heterogeneous devices (CPU + GPU + FPGA + AI SoCs), extracting reusable subsystems and stitching new designs top-down.
• Develop optimized CV and Edge AI software stacks using OpenCV (C/C++), and validate inference accuracy, bounding boxes, video sync, and sensor fusion.
• Tune and benchmark performance (latency, throughput, frame accuracy, pipeline stability, IO bottlenecks).
• Debug accuracy failures and runtime anomalies deterministically (confidence collapse, zero inference output, oversized bboxes, pipeline stalls, data corruption, precision loss).
• Develop or standardize application-level APIs that abstract device behavior for Orbits internal agents.
• Build or integrate Linux device drivers when required, working close to hardware interface bring-up.
• Work with DevOps teams to productionize real-hardware deployment flows.

• C/C++ expert with strong foundations in embedded and systems engineering.
• Hands-on experience building real-time video streaming + inference pipelines (GStreamer, V4L2).
• Experience delivering production Edge AI software with OpenCV in C/C++.
• Strong ability in performance tuning and deterministic accuracy debugging.
• Solid knowledge of Linux device stack and drivers.

Familiarity with high-speed hardware interfaces:

• Ethernet, PCIe
• USB, MIPI CSI-2/DPHY, RTSP
• Understanding of application partitioning across heterogeneous hardware.
• Comfortable working in a research + prototyping + productization loop.
• Team-first, self-driven, high-ownership mindset.

• Background in Automotive, Industrial IoT, Robotics, or silicon accelerator integration
• Prior experience leading R&D teams
• Speaking experience in embedded or Edge AI developer communities