Job Summary:

We are seeking a highly skilled AI Consultant with 36 years of experience and a postgraduate degree (Masters or higher). The ideal candidate will have demonstrated expertise in both Agentic AI and Computer Vision, able to build, train, deploy, and optimize deep learning models for image and text analysis in industrial settings. The role equally emphasizes modern NLP and vision, with a focus on cloud-native solutions and data-driven innovation.

Key Responsibilities:

Development & Solution Design:

- Design, develop, and optimize advanced Deep Learning models for:

1. Vision: Image Classification, Object Detection, Image Segmentation, Visual Anomaly Detection

2. Language: Text Understanding, Document Processing, Report Generation, Multimodal AI (image + text), Agentic workflow automation

- Develop and Deploy Agentic AI applications using Lang Graph, OpenAI SDK etc.

- Train and deploy computer vision pipelines and CNN models to automate quality inspection pipelines.

- Conduct comprehensive data analysis of both image and text datasets to support AI development and validation.

Collaboration & Innovation:

- Collaborate cross-functionally with product, engineering, and QA for robust solution delivery.

- Participate in system architecture, R&D, and proof-of-concept (PoC) initiatives in both vision and NLP domains.

- Contribute to technical documentation, code best practices, and AI performance monitoring.

Required Skills:

Education:

- Postgraduate degree (Masters or higher) in Computer Science, AI, Data Science, or relevant field.

Technical Skills:

- Deep Learning: Proficient with Python and major frameworks (TensorFlow, PyTorch).

- LLMs: Hands-on with Large Language Models (GPT, BERT, Llama or similar); prompt engineering and fine-tuning.

- Vision: Advanced experience in image processing and CNN-based computer vision.

- Libraries/Tools: OpenCV, NumPy, Pandas, Scikit-learn.

- Data Analysis: Deep experience with large, complex structured and unstructured datasets.

- Cloud: Strong in GCP deployment of AI models; comfortable with Docker, Kubernetes, REST APIs.

- MLOps: Familiarity with MLOps tools for orchestration and monitoring.

Preferred Qualifications:

- 38 years of relevant industry experience.

- Track record in industrial AI, automation, manufacturing, or quality inspection domains.

- Knowledge of edge AI, real-time inference, and multimodal systems.

Soft Skills:

- Strong analytical, problem-solving, and data interpretation skills.

- Excellent written and verbal communication, capable of explaining AI concepts to varied audiences.

- Team player with a drive for continuous learning and technology innovation.

Nice-to-Have Skills:

- MLOps pipeline automation.

- GPU optimization and inference acceleration (TensorRT, ONNX).

- Model compression, quantization, and edge deployment.

- Exposure to hyperspectral or optical imaging, or multi-language NLP.

Sample Use Cases:

- AI-driven defect and anomaly detection (image and text).

- Automated quality inspection of products and documentation.

- Intelligent analytics combining vision and LLMs for manufacturing or industrial operations.

- Real-time computer vision and language monitoring for industrial automation.