MLE Developer with MLOps, Passenger Experience Platform

About the Position

We are looking for a hands on MLE and AI Ops Engineer to design, deploy, and operate data and AI products end to end. You will focus on platform and operations work, including infrastructure, MLOps pipelines, observability, security, and cost management.

About the Project

The Passenger Experience Platform supports smarter and more reliable customer and commercial experiences through data and AI solutions. The team builds and serves ML and GenAI solutions on Google Cloud Platform using a containerized and infrastructure as code foundation, with AI assisted development as part of the daily workflow.

About the Team

You will collaborate with a Data and AI organization working across platform, products, and domain delivery. The team operates in an Agile environment and works cross functionally to make the platform reliable, scalable, and self service for business domains.

Responsibilities

• Design, deploy, and operate ML and GenAI services end to end
• Build and maintain MLOps pipelines and CI/CD standards for data and AI workloads
• Enable the Data and AI platform to be reliable, scalable, and consumable across business domains
• Own environment and product infrastructure using Terraform on Google Cloud Platform
• Instrument observability and monitoring for models, pipelines, and services
• Apply security, IAM, governance, and cost optimization practices across data and AI
• Use AI assisted development to accelerate and improve delivery

Requirements

• 4 plus years of experience in MLE, ML platform engineering, AI Ops engineering, or a closely related role
• Strong Python skills for services and data work using Pandas and FastAPI
• Hands on experience with MLOps across model deployment, model registry, serving, and monitoring
• Experience with GenAI engineering using LangChain, agents, MCP, vector databases, and response caching
• Experience with containerization and orchestration using Docker and Kubernetes
• Experience with infrastructure as code using Terraform and CI/CD pipelines for data and AI
• Cloud experience on Google Cloud Platform with BigQuery for analytical workloads
• Fluency in Spanish and intermediate English for documentation and international collaboration

Nice to Have

• Experience with observability tooling such as Prometheus, Grafana, or Datadog
• Knowledge of data platform fundamentals including pipeline orchestration, lakehouse or warehouse concepts, and SQL transformations
• Knowledge of security, IAM, and data governance practices
• Strong critical thinking, communication, and collaboration in cross functional teams

Technologies

Google Cloud Platform, BigQuery, Python, Pandas, FastAPI, LangChain, agents, MCP, vector databases, model registry, response caching, Docker, Kubernetes, Terraform, CI/CD, Prometheus, Grafana, Datadog, SQL