Adani Green Energy Group

About The Opportunity We are hiring for the Travel & Tourism / Travel Technology sector — a fast-moving environment that leverages data to optimise pricing, personalise customer experiences, and automate operations across booking, inventory and logistics platforms. This remote role (India) will focus on building production-ready machine learning systems that drive conversion, retention, and operational efficiency for online travel services. Role & Responsibilities Design, develop and productionise ML models for recommendation, personalization, dynamic pricing and demand forecasting to directly improve booking conversion and revenue. Build end-to-end ML pipelines: data ingestion, feature engineering, training, validation, deployment and monitoring with automation for retraining and drift detection. Collaborate with product, engineering and data teams to translate business requirements into measurable ML solutions and A/B experiments. Deploy models as scalable REST APIs or microservices using containerisation (Docker) and cloud infrastructure (AWS/GCP/Azure) with CI/CD practices. Implement robust evaluation, observability and alerting for model quality, latency and business impact metrics; troubleshoot production issues quickly. Document model decisions, maintain reproducible workflows and mentor junior engineers on engineering best practices and MLOps patterns. Skills & Qualifications Must-Have 3+ years in Machine Learning/AI engineering or closely related applied role, ideally with production deployments. Strong Python skills and hands-on experience with scikit-learn and at least one deep-learning framework (TensorFlow or PyTorch). Proven experience building recommendation systems, personalization pipelines or time-series forecasting models for demand/pricing. Practical knowledge of data engineering: SQL, ETL, feature stores, and working with large datasets (S3, BigQuery, Redshift, or equivalent). Experience deploying models as APIs/microservices, containerisation (Docker) and basic orchestration or serverless deployment experience. Familiarity with model monitoring, A/B testing, experiment design and tracking tools (MLflow, Airflow, or equivalent). Preferred Experience with MLOps platforms, Kubernetes, or managed ML services on AWS/GCP/Azure. Knowledge of NLP techniques for search and chat personalization, or experience with real-time inference systems. Previous exposure to travel-tech domain problems (inventory, scheduling, cancellation risk, pricing) is a plus. Benefits & Culture Highlights Fully remote role with flexible hours — collaborate with cross-functional teams across India. Opportunity to impact customer experience and revenue directly by shipping models from prototype to production. Learning-first culture: mentorship, technical ownership and room to drive MLOps and engineering standards. This role is ideal for a results-driven Machine Learning Engineer who wants to apply end-to-end ML skills to real-world travel problems — from personalization and pricing to forecasting and automation. Apply if you enjoy shipping production models, measuring business impact, and improving systems iteratively. Skills: ml,design,learning,data,scikit-learn,models