Job Title: Computer Vision & AI Solutions Engineer
Experience: 3–8 Years
Department: AI / Industrial Automation / R&D
Job Summary:
We are looking for a Computer Vision & AI Solutions Engineer to design, develop, and deploy AI-driven computer vision systems for real-time workplace safety, industrial automation, and smart surveillance. You will work on full-cycle vision AI solutions — from research and model training to edge deployment and integration with safety dashboards or alerting systems.
Key Responsibilities:
- Build and deploy computer vision models for object detection, PPE detection, fire/smoke detection, pose estimation, and zone monitoring.
- Develop end-to-end pipelines for processing live camera feeds (RTSP/IP/CCTV) in real-time.
- Optimize and deploy AI models on edge devices like NVIDIA Jetson, Intel Movidius, or Raspberry Pi.
- Integrate vision systems with backend alerting tools, safety dashboards, or IoT infrastructure.
- Work with image/video datasets for annotation, augmentation, training, and evaluation.
- Collaborate with hardware, IoT, and frontend teams to deliver seamless safety solutions.
- Ensure compliance with safety protocols and real-world deployment constraints.
- Document technical processes and support customer-facing technical teams with deployment guidance.
Required Skills and Experience:
- Strong proficiency in Python with experience using OpenCV, NumPy, and Pandas.
- Hands-on experience with deep learning frameworks such as PyTorch, TensorFlow, or Keras.
- Experience with real-time object detection models: YOLOv5/v8, SSD, Faster R-CNN, Mask R-CNN.
- Knowledge of edge AI deployment: NVIDIA Jetson (Nano/Xavier/Orin), TensorRT, ONNX, or OpenVINO.
- Familiarity with video streaming protocols and integration (RTSP, HTTP, etc.).
- Understanding of model optimization techniques (quantization, pruning).
- Good problem-solving and debugging skills in computer vision projects.
Preferred Qualifications:
- Experience in safety-critical environments (manufacturing, construction, logistics, oil & gas).
- Working knowledge of alerting systems, APIs (REST), MQTT, or cloud integration (AWS/GCP).
- Familiarity with annotation tools like CVAT, LabelImg, Roboflow, or custom tools.
- Prior experience building vision-based attendance systems, people counting, or access control AI.
- Exposure to hardware-camera integration and sensor fusion is a plus.
Soft Skills:
- Strong communication and collaboration abilities.
- Passionate about solving real-world safety challenges using AI.
- Ability to work independently and with cross-functional teams.
- Willingness to travel for onsite implementation or client support (if required).
Compensation: [Competitive Based on Experience]
Perks: [Remote Options, Performance Bonus, Hardware Support, Learning Budget]
Reports To: AI Team Lead / CTO
