Key Responsibilities :

AI Product Development :

- Lead the end-to-end lifecycle of AI-powered solutions, encompassing computer vision, NLP, and predictive modeling.

- Drive the development of innovative use cases in areas such as image enhancement, document intelligence, entity extraction, and automated data validation.

- Apply advanced deep learning techniques, transformer architectures, and foundation

- model fine-tuning for scalable solutions for real-world applications.

- Design scalable AI services integrated via REST APIs and microservices.

- Explore cutting-edge technologies like generative AI, multilingual AI, and biometric verification.

MLOps & AI Engineering :

- Build and maintain CI/CD pipelines for model training, deployment, and testing.

- Automate monitoring, retraining workflows, and ensure traceability for models and datasets.

- Utilize tools such as MLflow, Kubeflow, Airflow, Docker, and Kubernetes for production grade deployment.

NLP & Language Model Applications :

- Lead development of domain-specific language models and PoCs.

- Implement transformer-based architectures for tasks like summarization, semantic search, and QA systems.

- Fine-tune large language models (LLMs) for unstructured data insights.

- Integrate NLP modules into business workflows and real-time systems.

Engineering Leadership :

- Mentor ML engineers and software developers.

- Collaborate with cross-functional stakeholders on product and engineering roadmaps.

- Lead sprint planning, delivery oversight, and code/architecture reviews.