8.0 - 10.0 years

30 - 45 Lacs

bengaluru

Work from Office

Reimagine Travel decisions with the power of AI @ MakeMyTrip. MakeMyTrip has been AI/ML/Data/Platform powered organization. We are now shaping the future of travel for Bharat customers, with GenAI-centric innovations, leveraging SLMs, Vernacular STT/TTS, and travel content systems. Join us to take these systems, chatbots, Cx, content to next orbit of excellence. Responsibilities: Design, develop, and fine-tune multilingual Small Language Models (SLMs) with advanced AI capabilities for agentic applications such as travel destination expertise, Myra bot orchestration, hotel semantic search, and customer support bot assistance. Build custom Natural Language Inference (NLI) and reward-scoring models to improve preference-based SLM training (DPO, PPO, SteerLM etc), enhancing multi-agent response quality and relevance. Develop and implement active learning pipelines for data and models, for NLP, Named Entity Recognition (NER), conversational latent intent/concepts, travel-specific embeddings, and domain-specific SLM training for summarization, rephrasing, and planning. Architect and enhance conversational AI systems to dynamically adapt and comprehend concepts/intents, NLP, and NER tasks across multiple lines of business, supporting the Myra chatbot ecosystem. Drive end-to-end quality assurance through robust integration and experience testing, establishing objective evaluation metrics and leveraging A/B testing for performance optimization. Mentor and guide engineering teams in advanced SLM and Generative AI analytics, fostering growth and innovation. Collaborate across teams to deliver scalable solutions that impact millions of users, ensuring alignment with business goals. Focus on hosting and deploying Generative AI models on robust and efficient infrastructure to support large-scale operations. What You Bring: Deep experience in Natural Language Processing (NLP & NLI), tiny/small language models, base language model retraining (both transformer and BERT based architectures). Extensive experience in conversational NLP systems. Experience in SLM adaptor fine tuning, SFT training, SLM pruning (base and instruct models) Experience in retriever frameworks in Q&A bots. Experience in contrastive learning, graph learning based embedding methods with heterogenous features. Preferably experience in building NLP active learning pipelines. Demonstrable experience in scaling your models to large scale search systems is a plus. Very good critical reasoning skills, data centric NLP/NLI systems. Must have temperament and hunger to work in fast-paced environment.

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