Deep Learning Research Engineer

Research, Design, and Develop advanced Deep Learning models and novel Neural architectures.

Explore architectures beyond Transformers, including State Space Models (SSMs), Liquid Neural Networks (LNNs), and Hybrid approaches.

Design and implement Agentic AI systems, Recursive Reasoning Engines, and tool-augmented architectures.

Fine-tuning of models using PEFT (e.g. LoRA, QLoRA etc.), and Knowledge Distillation.

M.Tech./M.S./Ph.D. in AI/ML or related disciplines, preferably from a Tier 1 premier Research Institution.

Strong foundations in Linear Algebra, Probability, Statistics, Optimization, and Deep Learning algorithms.

Proficient in frameworks like PyTorch/JAX, with hands-on model development experience.

Demonstrated ability to implement, reproduce, and extend research papers, including building neural architectures from scratch.