AI Research Scientist

About the Role We are seeking exceptional AI Research Scientists to join our research team and contribute to the development of next-generation artificial intelligence technologies. This is a research-first role focused on designing novel AI algorithms, architectures, and mathematical frameworksnot simply applying existing models. As part of our team, you will work on cutting-edge research spanning Deep Learning, Reinforcement Learning, Large Language Models (LLMs), Agentic AI, Scientific Computing, Tensor Mathematics, and High-Performance Computing, contributing to research publications, patents, and next-generation AI products. Key Responsibilities - Conduct advanced research in Machine Learning, Deep Learning, Reinforcement Learning, Generative AI, and Agentic AI. - Design and develop novel neural network architectures and AI algorithms. - Build advanced AI models for large-scale spatial-temporal systems and other computationally intensive applications. - Develop high-performance tensor computation frameworks and optimize AI workloads for GPU acceleration. - Implement, reproduce, evaluate, and improve state-of-the-art research from leading AI conferences and journals. - Collaborate with researchers and engineers to translate research into scalable AI systems and products. - Contribute to research publications, patents, and innovative AI solutions. - Stay up to date with emerging research trends and identify opportunities for innovation. Required Qualifications - M.Tech., M.S. (Research), M.Sc., Ph.D., or final-year postgraduate student from premier institutions such as: - IITs - IISc - BITS Pilani - Leading NITs - Other reputed research institutions - Strong academic background in one or more of the following: - Computer Science - Artificial Intelligence - Mathematics / Applied Mathematics - Electrical Engineering - Computational Engineering - Theoretical Physics - Mathematical Physics - Related quantitative disciplines Technical Skills - Artificial Intelligence - Machine Learning - Deep Learning - Neural Networks - Reinforcement Learning - Large Language Models (LLMs) - Generative AI - Agentic AI - Mathematics - Linear Algebra - Tensor Algebra & Multilinear Algebra - Probability & Statistics - Optimization - Calculus - Programming & Frameworks - Python - PyTorch (preferred) - TensorFlow or JAX - Scientific Computing - Systems & Performance - GPU Programming - CUDA (preferred) - High-Performance Computing (HPC) - Distributed Deep Learning Preferred Research Experience - Tensor Decomposition - Geometric Deep Learning - Scientific Computing - High-Performance Computing (HPC) - GPU Optimization - Distributed Deep Learning - Large-Scale AI Systems - Research Publications (Preferred) - NeurIPS - ICML - ICLR - CVPR - ICCV - AAAI - IJCAI - ACLEMNLP - ICASSPIJ - CNN .