Lead Data Scientist

About UsRapidCue AI is an innovative platform built as a real-time AI sales copilot and autopilot, designed to enable smarter conversations and faster conversions in sales and customer support calls. It provides live support for sales representatives during calls and can also autonomously handle interactions when needed. By combining voice AI, large language models, and real-time intelligence, RapidCue AI helps teams improve speed, consistency, and performance at scale.We are building at the intersection of Generative AI, speech intelligence, and agentic automation to redefine how modern sales teams operate.Role DescriptionThis is a full-time, on-site role for a Data Scientist, based in Bengaluru. In this role, you will work on the development of advanced AI systems powering real-time sales intelligence, conversational automation, and decision support across voice-based workflows.You will contribute to building and improving Generative AI and machine learning solutions, including LLM-powered agents, speech-to-text pipelines, conversational intelligence, prompt orchestration, retrieval-augmented generation (RAG), and real-time recommendation systems. You will collaborate closely with product, engineering, and business teams to build scalable AI-first products that improve sales effectiveness and customer engagement.Your day-to-day responsibilities will include developing and testing production-ready AI models, designing agentic workflows, improving voice and language understanding systems, analyzing large datasets, and helping translate AI capabilities into measurable business impact.Key ResponsibilitiesBuild and improve GenAI-driven products for real-time sales assistance and autonomous voice interactionsDevelop systems involving LLMs, LangChain/LangGraph-style orchestration, agentic workflows, RAG pipelines, and prompt engineeringWork on speech-to-text, text-to-speech, speaker intelligence, call summarization, intent detection, and real-time conversation analysisBuild AI pipelines for live call assistance, next-best response generation, objection handling, lead qualification, and conversational automationDesign and deploy ML, NLP, and voice AI models for production use casesWork with structured and unstructured datasets including call transcripts, CRM data, conversation logs, and sales outcomesCollaborate with cross-functional teams to align AI capabilities with product and business goalsRun experiments, evaluate model performance, and continuously improve AI systemsContribute to scalable deployment practices with focus on latency, reliability, and real-time performanceStay updated with the latest advancements in LLMs, multimodal AI, speech AI, and agentic systemsPreferred Background / ExperienceStrong experience in Generative AI, Large Language Models (LLMs), and applied NLPHands-on experience with frameworks such as LangChain, LangGraph, LlamaIndex, or similar orchestration frameworksExperience building agentic AI systems involving reasoning, memory, tools, and workflow automationGood understanding of speech-to-text (ASR), voice intelligence, transcription systems, and conversational AIFamiliarity with real-time audio/voice pipelines for sales, support, or contact-center use casesExperience with RAG architectures, vector databases, embeddings, semantic search, and prompt optimizationStrong knowledge of machine learning, deep learning, predictive modeling, and statistical analysisExperience deploying AI/ML models into production with attention to latency, scalability, and monitoringExposure to MLOps / LLMOps, model evaluation, experimentation, and data pipelinesAbility to solve business problems through practical AI systems in fast-moving environmentsQualificationsStrong expertise in Data Science, Machine Learning, NLP, and applied statisticsProven experience working with LLMs, GenAI applications, and conversational AI systemsSolid understanding of statistical modeling, predictive analytics, and experimentationExperience working with large and complex datasets, especially text, audio, or conversational dataStrong analytical and problem-solving abilityGood communication and collaboration skills across teamsBachelor’s / Master’s degree in Data Science, Computer Science, Statistics, AI, Machine Learning, or a related field preferred

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