Deep Learning Engineer - Python/Tensorflow

Responsibilities :

- Design and implement deep learning models for image, video, object detection, and audio classification tasks.

- Apply and fine-tune CNN-based architectures and Vision Transformers (e. g., ViT, Swin).

- Integrate attention mechanisms (e. g., SE, CBAM, Transformer attention) into model architectures for enhanced feature learning.

- Utilize pretrained models for transfer learning and multi-task learning.

- Work with video data using spatio-temporal modeling techniques (e. g., 3D CNNs, temporal attention).

- Extract and process features from audio using spectrograms, MFCCs, or learned embeddings.

- Evaluate and optimize models for speed, accuracy, and robustness.

- Collaborate across teams to deploy models into production.

- Strong programming skills in Python, with experience in PyTorch or TensorFlow.

- Hands-on experience with CNNs, pretrained networks, and attention modules.

- Solid knowledge of Vision Transformers, including recent architectures (e. g., Swin, DeiT).

- Understanding of attention mechanisms (self-attention, cross-attention, squeeze-and-excitation, etc. ).

- Experience implementing and training object detection models (YOLO, SSD, Faster R-CNN, Retina Net, DETR).

- Experience in video analysis and temporal modelling.

- Strong grasp of audio classification workflows and features.

- Experience handling large-scale datasets and designing data pipelines.