3 Dialogue Systems Jobs

Job Summary: We are seeking an innovative and highly skilled Data Scientist (LLM & Generative AI) with 5+ years of experience in machine learning, natural language processing, and applied AI. The ideal candidate will have deep expertise in large language models (LLMs), prompt engineering, retrieval-augmented generation (RAG), and agentic AI approaches. This role involves developing intelligent, autonomous, and scalable AI solutions that leverage cutting-edge research in generative AI, transformers, and multi-agent systems. In addition, the candidate will be expected to collaborate closely with engineering teams to bring research into production. Key Responsibilities: Research, design, and implement advanced LLM-based solutions for NLP, knowledge retrieval, and reasoning tasks. Develop and fine-tune LLMs (e.g., GPT, LLaMA, Falcon, Claude) for domain-specific use cases. Apply agentic AI approaches (multi-agent systems, autonomous agents, decision-making pipelines) to real-world business challenges. Design and implement retrieval-augmented generation (RAG) pipelines to combine structured/unstructured data with LLM capabilities. Build and optimize prompt engineering frameworks, evaluation metrics, and automated testing for generative AI outputs. Collaborate with ML engineers to deploy models into scalable cloud environments (AWS/GCP/Azure). Work with cross-functional teams to integrate LLM-powered agents into applications, workflows, and customer-facing products. Stay up-to-date with the latest research in LLMs, generative AI, reinforcement learning, and agentic architectures. Mentor junior team members and contribute to building an internal knowledge base on applied AI best practices. Requirements: Must-Have Skills: 5+ years of experience in data science, ML, or AI research with a focus on NLP and deep learning. Strong experience working with transformer architectures (e.g., BERT, GPT, T5, LLaMA). Hands-on expertise in fine-tuning and deploying LLMs using frameworks like Hugging Face Transformers, LangChain, or Haystack. Deep understanding of agentic AI approaches, including orchestration, multi-agent workflows, and autonomous reasoning systems. Proficiency in Python and ML libraries (PyTorch, TensorFlow, Hugging Face, LangChain, Ray). Strong background in applied NLP techniques such as text classification, summarization, embeddings, semantic search, and dialogue systems. Experience building RAG pipelines with vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus). Familiarity with MLOps and cloud deployment (AWS Sagemaker, GCP Vertex AI, Azure ML). Nice-to-Have Skills: Knowledge of reinforcement learning (RLHF, RLAIF) for LLM optimization. Experience with multi-modal models (text, image, speech). Familiarity with graph databases and knowledge graphs for reasoning tasks. Contributions to open-source projects in NLP/LLM space. Understanding of privacy, security, and ethical considerations in generative AI. Location- remote Salary -25lpa Experience -5+years 6 months contract (extendable) Show more Show less

You are a highly skilled and motivated Robot AI Engineer with expertise in Natural Language Processing (NLP) and Action Mapping for autonomous robots. Your role involves developing and integrating cutting-edge AI and NLP models to enable robots to understand and execute natural language commands, as well as engage in meaningful interactions. As a senior team member, your focus will be on building dialogue systems, intent recognition, and command understanding by combining advanced language models with robotic action execution, resulting in intelligent and intuitive robotic systems. Your responsibilities include designing, implementing, and optimizing NLP algorithms to facilitate robots in understanding and processing complex human language. You will work on developing Transformer-based models, dialogue systems, and conversational AI to enhance robots" capabilities in engaging with users. Additionally, you will apply sequence models, Speech Recognition (ASR), and Text-to-Speech (TTS) systems to enable voice-based command understanding and responses. Furthermore, you will develop and integrate RAG (Retrieval-Augmented Generation) models to enhance robots" contextual understanding and accuracy in responses. Your role also involves enabling intent recognition for robot action mapping, contributing to multilingual NLP systems, collaborating with robotics teams, implementing Deep Learning Frameworks, and staying updated with advancements in NLP, AI, and robotics. To qualify for this role, you should have a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Robotics, or a related field, along with at least 5 years of experience in NLP, AI systems, and robotic action mapping. Proficiency in Transformer models, deep learning frameworks, Speech Recognition, Text-to-Speech systems, dialogue systems, and command understanding is essential. Strong programming skills in Python and familiarity with libraries like spaCy, NLTK, Transformers, and OpenAI GPT are required. Preferred qualifications include a PhD in NLP, AI, or Robotics, published work in major conferences, experience with Reinforcement Learning, ROS middleware, and contributions to open-source projects. This position is based in Navi Mumbai (Ghansoli) with a work-from-office policy for 5 days a week.,

As a Prompt Engineer in the Artificial Intelligence/R&D department, you will play a vital role in building, optimizing, and testing natural language prompts to enhance the performance of large language models like OpenAI GPT, Claude, and Gemini. Your primary responsibilities will involve designing, writing, and optimizing natural language prompts to address specific business or product challenges. Working alongside data scientists, product managers, and engineering teams, you will contribute to the development of high-quality AI prompt systems for real-world applications. Your role will require you to analyze and test the impact of different prompts on model output quality, collaborating closely with product and development teams to create deployable prompt templates and interface logic. Additionally, you will be involved in establishing prompt libraries and prompt engineering frameworks to enhance prompt reusability and scalability. Staying updated on the latest prompt engineering technologies and research papers will be crucial, as you transform these insights into practical applications. To excel in this role, you must demonstrate proficiency in utilizing mainstream large-scale language models such as GPT-4, Claude, or Gemini. Strong language expression and logical thinking skills, along with expertise in prompt tuning, few-shot learning, and chain-of-thought prompt engineering methods, are essential. A bachelor's degree in a relevant field (computer science, linguistics, cognitive science) is required, with a preference for candidates with strong English reading abilities to understand model documents and research papers. Candidates with experience in actual Large Language Model (LLM) application projects, mastery of Python programming for rapid prototyping, and familiarity with dialogue systems, search engines, knowledge graphs, and RAG technologies will be given bonus points. Understanding model fine-tuning, LoRA, and system prompt structure, as well as familiarity with tool chains like LangChain, LlamaIndex, and OpenAI Function Calling, will be advantageous. In return, we offer a competitive salary and bonus system, the chance to work with cutting-edge AI technology, flexible working hours, and remote work options. Join our team of technology enthusiasts and innovators to embark on a rewarding career journey.,