Director - Technology Development

4 days ago

New Delhi, India MakeMyTrip Full time

Job Title: Director — Technology Development (Personalization) Location: Bengaluru Experience: 15+ Years Function: Data Platform & PersonalizationWhy This Role Reimagine travel personalization at platform scale across Flights, Hotels, Holidays, Trains, and Activities. Own end-to-end personalization charter: engineering, data science, MLOps, and experimentation. Collaborate with ContextOS, Myra, and Experience Hub under the “One Brain, Many Adapters” vision.What You’ll Own Strategy & Roadmap: Drive 12–18 months personalization roadmap aligned to KPIs (growth, conversion, retention, experience). Platforms, Not Projects: Build reusable ranking/reco/decisioning platforms (feature/embedding store, real-time signals, policy/constraints, evaluation). ML in Production: Lead model lifecycle (user modeling, content understanding, candidate generation, re-ranking, optimization, bandits/RL) with clear SLOs. Experimentation & Causality: Scale A/B and bandit experimentation; ensure robust guardrails and uplift measurement. Privacy-First Personalization: Embed consent, PII handling, and privacy-by-design in data contracts; ensure regulatory compliance. Agentic & Real-Time Experiences: Integrate with ContextOS and Myra for explainable, grounded, actionable recommendations across channels. People & Org: Lead a 25–40 members team across Backend/Platform engineers, MLEs, DS/Applied Scientists, and Program; hire, coach, and build succession. Partnering & Influence: Collaborate with Product, Design, Marketing, Supply, Finance, and Legal; manage vendors/partners. Observability & Evals: Establish evaluation frameworks and operational excellence (SRE, On-call, RCA). Cost & Reliability: Own budgets, infra choices, and efficiency (GPU/CPU mix, caching, quantization, distillation).What You’ve Done 15+ years in consumer tech/platforms with 7+ years leading cross-functional Eng + DS/MLE teams. Delivered production ML (recommendations/ranking/search/ads/feeds) for millions of users with measurable uplift and strong SLOs. Built/owned feature & embedding stores, online feature serving, streaming pipelines, and A/B platforms. Deep hands-on expertise in large-scale backend (Java/Scala/Go) or applied ML (Python, PyTorch/TensorFlow) with architectural leadership. Experience with real-time systems (Kafka/PubSub, Flink/Spark Streaming), datastores (Redis, Cassandra/DynamoDB, Elasticsearch), MLOps (MLflow/Kube/Triton/Ray), and cloud (AWS/Azure/GCP). Proven implementation of privacy-by-design, data contracts, and governance in production pipelines. Strong product sense and storytelling; ability to align executives and mentor senior ICs and managers.Nice to Have Experience with multi-objective optimization, constrained ranking, or contextual bandits/RL. Familiarity with knowledge graphs/ontologies, retrieval/RAG, agentic workflows, LangGraph/LangChain, and LLM/agent evaluation frameworks. Experience in Indian consumer internet scale, marketplaces, or travel.

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