Scope of Work

Develop, build, and optimize deep learning models for various AI use cases.

Design and implement computer vision solutions such as image classification, object detection, OCR, tracking, and segmentation.

Develop multimodal AI models that combine multiple data types (e.g., text, image, video, audio).

Perform data preprocessing, feature engineering, and dataset curation for training models.

Train, evaluate, and fine-tune models using frameworks such as TensorFlow or PyTorch.

Deploy AI models into production environments and ensure scalability and performance.

Collaborate with cross-functional teams (product, backend, data, and business) to translate business needs into AI solutions.

Monitor model performance and perform continuous improvement (model retraining, tuning, etc.).

Document experiments, models, and technical processes.

Requirement

Bachelor’s degree in Computer Science, AI, Data Science, or related field.

Minimum 2–5 years experience in AI / Machine Learning / Deep Learning (adjustable).

Strong understanding of Deep Learning concepts: Neural networks (CNN, RNN, Transformer)

Model training, tuning, and evaluation

Experience in Computer Vision, including:

Image processing (OpenCV)

Object detection (YOLO, SSD, Faster R-CNN)

Image classification & segmentation

Experience in Multimodal AI:

Combining text, image, or audio inputs

Familiar with models like CLIP, multimodal transformers (value added)