About the opportunity:
Role: Principal Data Scientist - GenAI, Recommendation Personalization
Location: Bangalore

Experience Level: 8-10 years

About the function:

At MakeMyTrip (MMT), technology is at the heart ofeverything we do. As a leading player in the travel industry, we leveragecutting-edge solutions like AI, machine learning, and cloud infrastructure tocreate seamless and innovative travel experiences. We prioritize a tech-firstmindset, where our engineering teams lead the charge in transforming the waypeople travel.
Our culture encourages collaboration, creativity, andthought leadership, empowering engineers to challenge the status quo anddevelop impactful, game-changing solutions. At MMT, you'll work with the latesttechnologies, continually push boundaries, and have the chance to shape thefuture of travel.
Join us and become part of a forward-thinking, tech-drivenorganization that thrives on innovation and continuous learning.

About the Role:

We are looking for a Principal DataScientist to drive advanced AI/ML initiatives for large-scale consumer productswhile providing technical leadership to a team of Data Scientists. This is a hands-on technical leadership role for someonewith deep expertise across Generative AI, Large Language Models, RecommendationSystems, Personalization, Search, NLP, Information Retrieval, andRepresentation Learning. The successful candidate will remain deeply involvedin research, experimentation, modeling, and system design while leading thetechnical direction, architecture, and execution of complex AI/ML initiatives.
The role operates at the intersection of AI research andproduction engineering. The ideal candidate should be comfortable evaluatingstate-of-the-art research, designing novel ML architectures, runninglarge-scale experiments, and translating successful approaches into reliableand scalable production systems.
In addition to hands-on technical contributions, thecandidate will mentor Data Scientists, drive architecture and design reviews,establish ML best practices, and help raise the overall technical bar of theData Science organization.

What will you be doing:

- Architect, develop,



and productionize large-scale MachineLearning, Deep Learning, and Generative AI systems for consumer-facingapplications.
- Build personalization and recommendation systems usingtechniques such as Two-Tower architectures, neural retrieval, sequentialmodeling, representation learning, and learning-to-rank.
- Design, fine-tune, and post-train Large Language Models(LLMs) and Small Language Models (SLMs) using techniques such as SupervisedFine-Tuning (SFT), LoRA/PEFT, preference optimization, GRPO, RLHF, and RLVR.
- Design custom reward functions, reward models, andevaluation signals for reinforcement-learning-based LLM post-training,incorporating task-specific, quality, factuality, and preference signals.
Develop embedding and representation-learning systemsusing contrastive learning, self-supervised learning, sequence modeling, andrelated deep-learning techniques.
- Build semantic search, retrieval, and ranking systemsleveraging dense retrieval, vector search, multi-vector retrieval, reranking,and modern neural Information Retrieval techniques.
- Explore and develop RAG, Graph RAG, Knowledge Graph,Agentic AI, tool-calling, and multi-step reasoning systems for complex AIapplications.
- Build scalable synthetic-data generation, dataaugmentation, and model-training pipelines for LLM and ML applications.
- Design robust offline and online evaluation frameworks forGenerative AI, retrieval, ranking, recommendation, and personalization systems,including A/B experimentation.
- Optimize AI/ML systems across model quality, inferencelatency, throughput, scalability, reliability, compute, and serving cost.
- Translate ambiguous business problems into well-defined MLproblems and independently drive them through problem formulation, research,experimentation, architecture, productionization,



and measurement.
- Partner closely with Product, Engineering, Analytics, andData teams to deliver AI/ML capabilities with measurable customer and businessimpact.
- Provide technical leadership to a team of Data Scientiststhrough architecture reviews, technical guidance, mentoring, experimentationstrategy, and ML engineering best practices.
- Continuously evaluate emerging AI/ML research anddetermine its applicability to real-world problems and production systems.

Qualification Experience:

- 8+ years of industry experience in Machine Learning, DataScience, Applied AI, NLP, Information Retrieval, Recommendation Systems, orrelated areas.
- Strong hands-on expertise in Python and moderndeep-learning frameworks such as PyTorch and/or TensorFlow.
- Deep understanding of Transformers, attention mechanisms,embeddings, representation learning, and modern deep-learning architectures.
- Strong expertise across multiple areas such as GenerativeAI/LLMs, Recommendation Systems, Personalization, Search Ranking, NLP,Information Retrieval, and Representation Learning.
- Hands-on experience across the modern LLM lifecycle,including SFT, PEFT techniques such as LoRA, preference optimization, rewardmodeling, RL-based post-training approaches such as GRPO/RLHF/RLVR, evaluation,and inference.
- Experience designing and deploying production-grade MLsystems at scale and working with large-scale behavioral, interaction, ortransactional datasets.
- Strong system-design skills with the ability to makepractical trade-offs across model quality, latency, compute, scalability,reliability, and cost.
- Demonstrated ability to provide technical direction andmentor Data Scientists and ML Engineers.
- Solid communication and collaboration skills, with theability to work effectively across Product, Engineering, Data, Analytics, andbusiness stakeholders.
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Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Principal Data Scientist (Bengaluru)
🏢 MakeMyTrip
📍 Bengaluru