Responsibilities:
1) Research, design, and develop computer vision and deep learning models for image and video understanding.
2) Work on Generative AI systems, including:
a. Large Language Models (LLMs)
b. Vision-Language Models (VLMs)
c. Multimodal and generative architectures.
3) 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) Collaborate with cross-functional teams and clearly communicate progress and results.
Requirements:
1) Degree in Electronic/Computer Engineering/Computer Science/AI or related discipline
2) Strong foundation in Computer Vision and Deep Learning.
3) Hands-on experience with Generative AI, including LLMs, VLMs, or related multimodal models.
4) Experience in:
a. Model training and fine-tuning with real-world datasets
b. Deployment and inference optimization
5) Strong programming skills in Python, C++
6) Solid understanding of software engineering principles and application development.
7) Ability to work independently, manage projects end-to-end, and learn new technologies quickly.
8) Strong problem-solving, communication, and teamwork skills.
Preferred / Added Advantages:
- Experience with Pytorch / TensorFlow, OpenCV, Hugging Face ecosystem.
- 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.
