Research Core AI Scientist ? Foundation Models / Deep Learning

Job Description

Research Scientist ? Core AI - Lead Locations: Bangalore / Delhi-NCR / Trivandrum / Mumbai (Onsite) Experience : 10+ years What you?ll do Invent new methods in deep learning/foundation models (architectures, training objectives, optimization, alignment, evaluation). Own the research cycle end-to-end: literature review ? hypothesis ? method design ? experiments & ablations ? paper ? open-source artifacts ? transfer to product teams. Build rigorous evaluation : benchmarks, baselines, statistical tests, reproducibility (seeds, configs, logs). Collaborate with engineers to scale training & inference (distributed training, profiling, efficiency). Must-have (strict) PhD (preferred) or MS (Research) in AI/ML/CS First-author, peer-reviewed papers proposing new models/algorithms/objectives in top venues (NeurIPS/ICML/ICLR/ACL/EMNLP/TMLR/JMLR) within the last 3?4 years. Demonstrated from-scratch development for tabular/structured problems: e.g., novel sequence/tabular transformers, time-series objectives, structure-aware pretraining, new loss/regularizers, or agentic reasoning/evaluation methods beyond RAG/prompting. Strong math & systems: linear algebra, probability, optimization; PyTorch or JAX, distributed training, experiment tracking; clean research code and ablation hygiene. Agentic AI (required exposure) Research experience with agentic systems (single or multi-agent) covering planning, tool-calling, self-critique/evaluators, safety/guardrails , or learning-to-reason ?with novelty beyond wiring APIs. Evidence of method contributions (e.g., new planner/objective, coordination mechanism, evaluator metric) on structured/tabular tasks. Nice to have Work on efficiency (flash-attn, quantization, LoRA/QLoRA, distillation), alignment (RLHF/DPO/ORPO), or multimodal (vision-language/audio). Experience designing scaling laws , data curriculum, or safety/robustness evaluations. We are not looking for Computer-vision-heavy profiles (image/video-centric portfolios). Roles limited to prompting/RAG/agent wiring without novel methods or first-author papers. Only application/survey papers; no code or ablations to reproduce claims. Interested candidates can share resume to [email protected]