Lead AI Scientist

Description :

Roles and 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.

Leadership & Soft Skills :

- Communication- Clear verbal and written communication to collaborate with technical and non-technical colleagues

- Time management- Ability to prioritize critical issues and projects to ensure SLAs are met

- Problem-solving- Applying logic and analytical thinking to diagnose and troubleshoot both simple and complex issues

- Documentation- Maintaining detailed and up-to-date documentation of configurations, issues, processes, and resolutions

- Teamwork- Coordinating with IT teams, managers, and end-users to deliver technology solutions

- Learning- Enthusiasm for continuously upgrading skills and keeping up with technological advances

Qualification and Experience :

- Masters/Ph.D. in Computer Science, AI/ML, Computer Vision, or related fields.

- 6-10 years of industry or research experience in deep learning and AI systems.

- Strong expertise in PyTorch, TensorFlow, ONNX, CUDA, transformers, multimodal learning, and generative models.