Senior Research Scientist NLP, Foundation Models & Agentic AI

About the Role

• We are seeking a world-class Research Scientist to lead cutting-edge research and
• development in Natural Language Processing (NLP), Foundation Models, Generative AI,
• Reasoning Systems, Agentic AI, and Multimodal Intelligence.
• The ideal candidate combines strong academic research credentials with hands-on
• experience building and deploying advanced AI systems. This role requires deep expertise
• in modern machine learning, large-scale model development, scientific experimentation, and
• translating research breakthroughs into impactful products and platforms.
• The candidate will work at the intersection of fundamental research and applied AI
• innovation, contributing to next-generation intelligent systems that can reason, plan, learn,
• retrieve knowledge, and interact autonomously across multiple modalities.

Key Responsibilities

• Research & Innovation
• ● Conduct original research in NLP, Deep Learning, Generative AI, Foundation Models,
• Agentic AI, and Multimodal AI.
• ● Design and develop novel architectures, algorithms, and training methodologies for
• large-scale AI systems.
• ● Investigate emerging areas such as:
• ○ Reasoning Models
• ○ Agentic Workflows
• ○ Multi-Agent Systems
• ○ Long-Context LLMs
• ○ Retrieval-Augmented Generation (RAG)
• ○ Memory-Augmented Systems
• ○ AI Alignment & Safety
• ○ Synthetic Data Generation
• ○ Knowledge Grounding
• ○ Continual Learning
• Foundation Model Development
• ● Design, train, fine-tune, and evaluate large language models and foundation models.
• ● Develop efficient training and inference methodologies.
• ● Work on instruction tuning, alignment, preference optimization, and reinforcement
• learning-based approaches.
• ● Build scalable model pipelines for experimentation and deployment.
• AI Product Development
• ● Translate research innovations into deployable AI capabilities.
• ● Collaborate with engineering and product teams to productionize research outcomes.
• ● Design end-to-end AI solutions covering:
• ○ Data collection
• ○ Data curation
• ○ Model training
• ○ Evaluation
• ○ Deployment
• ○ Monitoring
• ○ Continuous improvement
• Evaluation & Benchmarking
• ● Develop robust evaluation methodologies for:
• ○ Reasoning
• ○ Hallucination Reduction
• ○ Agent Performance
• ○ Retrieval Quality
• ○ Safety
• ○ User Experience
• ● Design benchmarks and experimental frameworks for model comparison and
• validation.
• Leadership & Collaboration
• ● Mentor junior researchers and ML engineers.
• ● Drive technical strategy for advanced AI initiatives.
• ● Publish research findings in leading conferences and journals.
• ● Represent the organization in academic, research, and industry forums.

Required Qualifications

• Education
• ● PhD or M.Tech/MS in Computer Science, Artificial Intelligence, Machine Learning,
• NLP, Data Science, Computational Linguistics, or related fields.
• ● Candidates from premier institutions such as IITs, IISc, IIITs, top international
• universities, or equivalent research institutions are strongly preferred.
• Research Publications
• Must have a proven publication record in leading AI/ML/NLP conferences and journals,
• including but not limited to:
• ● NeurIPS
• ● ICML
• ● ICLR
• ● ACL
• ● EMNLP
• ● NAACL
• ● COLM
• ● Equivalent top-tier international conferences and journals
• Preferred:
• ● First-author publications
• ● Highly cited publications
• ● Best paper nominations or awards
• Core Technical Skills
• Machine Learning & Deep Learning
• ● Advanced Machine Learning
• ● Deep Learning
• ● Representation Learning
• ● Self-Supervised Learning
• ● Transfer Learning
• ● Optimization Techniques
• ● Statistical Learning Theory
• NLP & LLMs
• ● Transformers
• ● Attention Mechanisms
• ● Encoder-Decoder Architectures
• ● Foundation Models
• ● Large Language Models
• ● Instruction Tuning
• ● Prompt Engineering
• ● Long-Context Architectures
• ● Mixture of Experts (MoE)
• ● Parameter Efficient Fine-Tuning (PEFT)
• Reasoning & Agentic AI
• ● Chain-of-Thought Reasoning
• ● Test-Time Compute Optimization
• ● Reflection & Self-Correction
• ● Agent Frameworks
• ● Multi-Agent Systems
• ● Planning and Tool Usage
• ● Autonomous Decision-Making Systems
• ● Workflow Orchestration
• Retrieval & Knowledge Systems
• ● Retrieval-Augmented Generation (RAG)
• ● Dense Retrieval
• ● Hybrid Search
• ● Knowledge Graphs
• ● Semantic Search
• ● Vector Databases
• ● Memory Systems
• ● Knowledge Grounding
• Reinforcement Learning
• ● RLHF
• ● RLAIF
• ● DPO
• ● GRPO
• ● Reward Modeling
• ● Preference Optimization
• Multimodal AI
• ● Vision-Language Models
• ● Image Understanding
• ● Audio Understanding
• ● Video Understanding
• ● Multimodal Retrieval
• ● Cross-Modal Learning
• Programming & Engineering Skills
• ● Python (Expert)
• ● PyTorch (Expert)
• ● TensorFlow/JAX (Preferred)
• ● Kubernetes
• ● Docker
• ● Linux
• AI Infrastructure Experience
• Strong hands-on experience in:
• ● Training large-scale models
• ● Multi-GPU environments
• ● Distributed systems
• ● Model optimization
• ● Inference acceleration
• ● GPU utilization optimization
• ● Production AI systems
• ● MLOps platforms
• ● Cloud AI infrastructure

Preferred Qualifications

• Research Recognition
• Preference will be given to candidates who have received prestigious fellowships, awards, or
• recognitions such as:
• ● Prime Ministers Research Fellowship (PMRF)
• ● Google PhD Fellowship
• ● Microsoft Research Fellowship
• ● NVIDIA Fellowship
• ● JRF/SRF Research Fellowships
• ● National or International Research Awards
• ● Outstanding Thesis Awards
• Industry & Product Impact
• ● Experience building production-grade AI products.
• ● Proven track record of translating research into business impact.
• ● Experience leading AI initiatives from concept to deployment.
• ● Contributions to widely used AI platforms or products.
• OR Open Source & Community Contributions
• ● Significant GitHub contributions.
• ● Maintainer or contributor to major AI frameworks.
• ● Open-source model releases.
• ● Research toolkits and benchmark contributions.
• OR Intellectual Property
• ● Patents in AI, NLP, Deep Learning, or Generative AI.
• ● Technology transfer or commercialization experience.

What Will Make You Stand Out

• ● Publications in NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL, or COLM.
• ● PMRF or equivalent prestigious fellowship.
• ● Experience training or contributing to foundation models with billions of parameters.
• ● Strong publication and citation record.
• ● Experience in Agentic AI and Reasoning Systems.
• ● Demonstrated ability to build and deploy advanced AI products.
• ● Open-source leadership and research community engagement.
• ● Ability to bridge scientific research and product innovation.