1. 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
2. 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.
3. 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
Skills Required
- Strong experience in Linux application development on embedded and server platforms
- Proficiency in modern C++ standards 14, 17, or 20
- Solid Python experience for scripting, tooling, and service development
- Knowledge of distributed systems and message-bus architectures such as MQTT or Kafka
- Hands-on experience designing and implementing REST and gRPC APIs
- Familiarity with CI/CD workflows and GitHub Actions, CMake, Docker, and Kubernetes
- Strong unit testing skills using GTest and pytest
- Experience with GStreamer and custom cross-platform plugin development
- Understanding of inference runtimes such as ONNX Runtime, TensorRT, or OpenVINO
- Exposure to computer vision and AI workloads on edge hardware including NPU, GPU, or DLA
- Familiarity with RTSP and shared-memory buffer integrations
- Understanding of computer vision algorithms including object detection, tracking, and segmentation
- Experience with MLOps tools for model monitoring, issue detection, and retraining workflows
- Hands-on experience with MLflow for experiment tracking and model registry
- Knowledge of dataset versioning tools such as DVC or equivalents
- Familiarity with observability tools such as Evidently, Grafana, and Prometheus
- 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, or CV72 and EazyAI or CVflow toolchains
- Understanding of advanced computer vision algorithms such as pose estimation and re-identification
- Experience with Label Studio for annotation project setup and model-assisted labeling
- Integration experience with LLM/VLM models such as LLaVA or Qwen-VL in real-time pipelines or agent-based systems
