Senior Software Engineer-Computer vision

We are seeking a Computer Vision/AI Engineer to research architect and deploy state-of-the-art vision models for high-throughput low-latency computer vision this role you will work on problems spanning real-time object detection multi-class classification tracking and instance segmentation. You will bridge cutting-edge applied research with edge/cloud production engineeringexperimenting with advanced CNN backbones Vision Transformers (ViTs) and multimodal architectures while optimizing inference speed for real-world constraint.

Technical Responsibilities

• Evaluate benchmark and adapt frontier vision architectures (e.g. YOLO variants R-CNN ViTs Transformers MobileNet backbones).
• Design train and fine-tune computer vision models using PyTorch TorchVision etc.
• Architect data preprocessing augmentation and annotation workflows for imbalanced and noisy visual datasets.
• Optimize deep learning models for strict latency/throughput budgets using TensorRT ONNX Runtime DeepStream etc.
• Apply model compression techniques including post-training quantization (INT8/FP16) and knowledge distillation.
• Implement active learning loops and continuous monitoring systems to track data drift and edge-case model failures in production.

Minimum Qualification

• Bachelors degree in software engineering/ Computer Science or related discipline with 5 years of work experience or Masters in relevant disciplines with 5 years of experience or PhD degree in relevant disciplines with 2 years of work experience.

Preferred Qualifications

• 5 years hands-on experience designing and training computer vision models in production or applied research environments.
• Proficiency in Python and PyTorch (or TensorFlow); solid foundation in OpenCV and NumPy.
• Proficiency in end-to-end MLOps practices.
• In-depth theoretical and practical grasp of
  • Classic & modern CNNs (ResNet EfficientNet ConvNeXt).
  • Vision Transformers & attention mechanisms (ViT Swin DETR RT-DETR).
  • Modern real-time detector architectures (YOLO* RT-DETR SSD).
• Excellent communication skills with the ability to work cross-team.

Good to have

Experience with video streaming protocols and pipelines (RTSP WebRTC GStreamer FFmpeg or NVIDIA DeepStream).