Research Scientist - Applied AI in भारत

About the Role:We are looking for a Research Engineer to build the next generation of AI agents capable of solving complex business problems through reasoning, retrieval, and multi-step decision https://jobeax.com/link/exSHKQn8iLR41V8n'll work on challenging research problems involving LLM agents, reinforcement learning, retrieval systems, evaluation frameworks, and continual learning. This role is ideal for engineers who enjoy experimenting with cutting-edge AI techniques and shipping production-ready https://jobeax.com/link/z6z9Jc0Aq7eC6CI7 you have experience building intelligent AI agents, training LLMs, designing evaluation pipelines, and improving model behavior through experimentation, we'd love to hear from https://jobeax.com/link/36VMSRBeaftrHJdU Responsibilities:- Design and improve agentic AI systems capable of complex multi-step reasoning.- Build intelligent tool-use strategies, planning mechanisms, and multi-agent workflows.- Develop advanced context engineering and memory management techniques for AI agents.- Design automated evaluation frameworks, benchmarks, and regression testing pipelines for LLM applications.- Train and fine-tune large language models using techniques such as LoRA, QLoRA, RLHF, DPO, GRPO, and SFT.- Research and implement reinforcement learning approaches for improving agent reasoning and decision-making.- Build retrieval systems using dense retrieval, hybrid search, reranking, GraphRAG, and knowledge graphs.- Develop explainable scoring models and prediction systems from structured and unstructured data.- Collaborate with engineering and research teams to rapidly prototype, evaluate, and deploy AI solutions into https://jobeax.com/link/egKNM4oFydFwC1F9 Skills:- Strong Python programming skills.- Hands-on experience with PyTorch and Hugging Face Transformers.- Experience building AI Agents or Multi-Agent systems.- Deep understanding of LLM fine-tuning and optimization techniques.- Experience with RLHF, DPO, PPO, ORPO, GRPO, or similar preference optimization methods.- Strong knowledge of Information Retrieval, Search, RAG, Hybrid Retrieval, or GraphRAG.- Experience with Agentic Memory, Context Engineering, or Knowledge Graphs.- Experience designing LLM evaluation frameworks, benchmarking systems, and automated evaluation pipelines.- Knowledge of Continual Learning or Lifelong Learning techniques.- Experience with Knowledge Distillation for language or retrieval models.- Strong understanding of model behavior analysis and https://jobeax.com/link/MzMXhiBqXmtVkCki Skills:- LangGraph, DSPy, OpenAI SDK, Anthropic SDK.- vLLM, DeepSpeed, TRL, Unsloth.- Vector Databases (Pinecone, Weaviate, Milvus, Qdrant).- Neo4j or Knowledge Graph technologies.- Ray, Kafka, Docker, Kubernetes.- FastAPI, AWS or GCP.- MLflow, Weights & Biases, Arize, https://jobeax.com/link/aTIVGAIR2CLKVnB2 Qualifications:- Experience building production-grade AI agents.- Experience with retrieval models, ranking systems, or enterprise search.- Publications in top-tier AI/ML conferences are a strong plus.- MS or PhD in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Mathematics, or a related quantitative https://jobeax.com/link/VhnSvqZ2NPpYeFdA Join?:- Work on cutting-edge Agentic AI and LLM research.- Solve challenging real-world AI problems at scale.- Collaborate with a highly technical engineering and research team.- High ownership, rapid innovation, and strong growth opportunities.- Competitive compensation and benefits. (ref:hirist.tech)