Responsibilities:
1)Â Â Â Research, design, and develop computer vision and deep learning models for image and video understanding.
2)Â Â Â Work on Generative AI systems, including:
a.   Large Language Models (LLMs)
b.   Vision-Language Models (VLMs)
c.    Multimodal and generative architectures.
3)Â Â Â Develop and own the full AI lifecycle:
a.   Data preparation and experimentation
b.   Model training and fine-tuning
c.    Evaluation, optimization, and benchmarking
d.   Deployment to local, edge, or cloud environments.
4)Â Â Â Collaborate with cross-functional teams and clearly communicate progress and results.
Requirements:
1)Â Â Â Degree in Electronic/Computer Engineering/Computer Science/AI or related discipline
2)Â Â Â Strong foundation in Computer Vision and Deep Learning.
3)Â Â Â Hands-on experience with Generative AI, including LLMs, VLMs, or related multimodal models.
4)Â Â Â Experience in:
a.   Model training and fine-tuning with real-world datasets
b.   Deployment and inference optimization
5)Â Â Â Strong programming skills in Python, C++
6)Â Â Â Solid understanding of software engineering principles and application development.
7)Â Â Â Ability to work independently, manage projects end-to-end, and learn new technologies quickly.
8)Â Â Â Strong problem-solving, communication, and teamwork skills.
Preferred / Added Advantages:
- Experience with Pytorch / TensorFlow, OpenCV, Hugging Face ecosystem.
-Â Exposure to Video models, Temporal modelling, or Multimodal transformers.
- Experience with cloud, edge, or on-device deployment.
- Familiarity with Docker, REST APIs, FastAPI/Flask, or similar frameworks.
- Prior experience with:
o  Publications (journals, conferences)
o  AI competitions (e.g., Kaggle, CV challenges)
o  Open-source contributions or research prototypes.