Embedded Engr II

Software Engineering

• Strong experience in Linux application development on both embedded and server platforms
• Proficiency in modern C++ (14/17/20)
• Solid Python experience for scripting, tooling, and service development
• Knowledge of distributed systems and message-bus architectures (e. g. , MQTT, Kafka)
• Hands-on experience with REST and gRPC API design and implementation.
• Familiarity with CI/CD workflows and tools such as GitHub Actions, CMake, Docker, and Kubernetes
• Strong unit testing skills using frameworks such as GTest and pytest

Video Analytics & Embedded AI

• Experience with GStreamer and custom plugin development for cross-platform.
• Understanding of inference runtimes such as ONNX Runtime, TensorRT, or OpenVINO
• Exposure to CV/AI workloads on edge hardware (NPU, GPU, DLA)
• Familiarity with RTSP and shared-memory buffer integrations
• Understanding of computer vision algorithms such as object detection, object tracking, and segmentation etc.

MLOps

• Experience with MLOps tools for model monitoring, issue detection, and retraining workflows
• Hands-on with MLflow for experiment tracking and model registry
• Knowledge of dataset versioning tools like DVC or equivalents
• Familiarity with observability tools such as Evidently, Grafana, and Prometheus

Nice to Have

• Experience with video analytics development.
• Experience developing custom Node-RED nodes or packaging flows.
• Background in physical security, VMS/NVR systems, or surveillance analytics
• Hands-on experience with Ambarella SoCs (CV25 / CV28 / CV72) and EazyAI / CVflow toolchains
• Understanding of advanced CV algorithms (e. g. , pose estimation, re-identification algorithms)
• Experience with Label Studio for annotation project setup and model-assisted labeling
• Integration experience with LLM/VLM models (e. g. , LLaVA, Qwen-VL) in real-time data pipelines or agent-based systems

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