Your Profile & DNA:We are looking for an experienced Machine Learning Engineer with strong MLOps expertise to build and operate production-grade ML solutions for ancillary product pricing, including seats, bags, extra legroom, and paid fare upgrades.This is a hands-on role covering the full ML lifecycle — from research and model development to deployment, monitoring, retraining, and optimization.

• Roles & ResponsibilitiesDevelop and maintain machine learning models for pricing and revenue optimization
• Design and implement end-to-end ML pipelines, including training, retraining, validation, deployment, and monitoring
• Productionize ML models with a strong focus on reliability, scalability, and low latency
• Continuously monitor and optimize production ML models
• Work with GCP, including BigQuery and Vertex AI
• Lead the MLOps practices within the team
• Design and optimize scalable ML architectures
• Build and maintain CI/CD pipelines and automated testing
• Manage infrastructure using Terraform
• Containerize applications and ML workloads using Docker
• Develop CI/CD automation using GitHub Actions
• Ensure solutions follow internal engineering, quality, security, and operational standards

• Qualification & ExperienceA Bachelor's or Master's Degree or equivalent.
• Strong experience in Machine Learning Engineering
• Solid hands-on MLOps experience
• Experience taking ML models from development to production
• Strong understanding of ML lifecycle, model deployment, retraining, and monitoring
• Experience with GCP
• Hands-on experience with BigQuery
• Experience with Vertex AI
• Strong Terraform experience
• Experience with Docker
• Strong knowledge of CI/CD and GitHub Actions
• Experience with automated testing
• Strong understanding of ML architecture and optimization
• Experience building low-latency, scalable production solutions