Description :

Responsibilities :

- AI Research & Innovation :

- Lead research in deep learning, computer vision, generative AI, transformers, and multimodal learning, Knowledge Distillation

- Develop novel algorithms for biometric spoof detection, facial/iris/fingerprint recognition, synthetic data generation, and cross-sensor generalisation.

- Evaluate emerging AI methodologies such as diffusion models, GNNs, self-supervised learning, reinforcement learning, and multimodal LVMs.

Architecture & System Design :

- Architect large-scale AI systems for cloud + edge deployment, ensuring performance, scalability, and reliability.

- Define model pipelines including data ingestion, preprocessing, training, evaluation, deployment, and monitoring.

- Lead architecture decisions for transformer-based vision models, multi-task learning systems, and hybrid cloud-edge AI platforms.

Model Development & Optimization :

- Build high-performance models using PyTorch, TensorFlow, ONNX, OpenVINO, TensorRT, and distributed training frameworks.

- Optimize large models for real-time inference (quantization, pruning, distillation, TensorRT tuning).

- Ensure robustness, security, and generalizability of AI models across devices, sensors, and domains.

Cross-Functional Leadership :

- Collaborate with product, engineering, and hardware teams to develop production-grade AI solutions.

- Mentor Senior/Junior AI Scientists and Engineers.

- Lead AI reviews, research discussions, peer reviews, and innovation planning.

AI Governance & Strategy :

- Drive AI roadmap, research milestones, publications, patents, and benchmarking.

- Implement Responsible AI principles, risk evaluation, bias detection, and model governance.