Vision AI Engineer

Band: E2

Responsibilities:
- Traditional AI Development:
- Implement and enhance people analytics solutions using AI.
- Develop and deploy object analytics models for various use cases.
- Drive the creation and optimization of traditional AI-based solutions.

- Generative AI Development:
- Work on Llava-based Gen AI analytics for descriptive insights.
- Develop advanced descriptive analytics using Vision-based Gen AI engineering.

Required Skills and Experience:

- Technical Expertise in Vision AI:
- Proficient in image processing and computer vision technologies.
- Hands-on experience with frameworks like OpenCV, TensorFlow, PyTorch, YOLO, and OpenVINO.

- Generative AI Expertise:
- Experience in Vision-based Gen AI engineering, especially with Llava models.
- Knowledge of multi-modal AI models encompassing vision, voice, and text.
- Proficiency in prompt engineering.

- Cloud Technologies:
- Familiarity with AWS, Azure, or Google Cloud Platform for AI/ML deployment.

- Development Methodologies:
- Strong understanding of software development methodologies and best practices.

Preferred Qualifications:
- Prior experience in Vision AI or Generative AI projects.
- Excellent problem-solving skills and the ability to work on cutting-edge AI solutions.
- Strong communication and collaboration skills.