Computer Vision Expert - Deep Learning in Bangalore, भारत

Key Responsibilities :- Lead the design and development of computer vision and machine learning solutions across object detection, image segmentation, classification, pose estimation, OCR, and tracking.- Evaluate and fine-tune pre-trained architectures such as ResNet, YOLO, ViT, DETR, SAM, and CLIP based on data availability and business use cases.- Design, develop, and optimize deep learning models using PyTorch and TensorFlow.- Leverage computer vision libraries and frameworks including OpenCV, Detectron2, MMDetection, Hugging Face Transformers, and timm.- Design or adapt CNNs, Vision Transformers, GANs, diffusion models, and other architectures for specific business and technical requirements.- Apply transfer learning and parameter-efficient fine-tuning techniques such as LoRA and adapters to efficiently adapt large and foundation models.- Build end-to-end data pipelines covering data collection, annotation, augmentation, and synthetic data generation using tools such as CVAT and Labelbox.- Optimize models for production using quantization, pruning, and knowledge distillation.- Deploy models using TensorRT, ONNX, OpenVINO, and edge-device platforms.- Establish and implement MLOps practices including experiment tracking, model versioning, ML CI/CD, and production monitoring using tools such as MLflow and Weights & Biases.- Work with cloud platforms such as AWS, GCP, and Azure and containerization technologies including Docker and Kubernetes.- Explore and implement sensor-fusion and multimodal solutions involving LiDAR, depth cameras, and other sensor data where applicable.- Lead technical reviews, establish engineering best practices, and ensure high-quality, maintainable https://jobeax.com/link/xxrxdsdqLMRIj7tT & Soft Skills :- Proven experience leading and mentoring teams of Computer Vision / ML Engineers.- Strong experience conducting code reviews and driving technical growth within the team.- Ability to evaluate build-vs-fine-tune-vs-buy trade-offs and define realistic technical roadmaps.- Proven track record of taking ML/CV models from prototype to production at scale.- Strong cross-functional collaboration with Product, Data, and Engineering teams.- Ability to stay current with computer vision research, emerging foundation models, and industry developments.- Strong communication skills with the ability to explain complex technical concepts and trade-offs to technical and non-technical stakeholders. Preferred Skills :- Experience with LiDAR, depth cameras, or multimodal/sensor-fusion applications.- Experience deploying computer vision models on edge devices.- Strong understanding of emerging vision foundation models and practical approaches to model adaptation and deployment. (ref:hirist.tech)