
Senior Back-End/MLOps Engineer - Real-Estate (Mexico)
About this role
Senior Back-End/MLOps Engineer - Real-Estate is a full-time position based in Mexico City that suits an experienced software professional looking to build scalable backend systems and machine learning pipelines for a real estate technology platform. Truelogic connects nearshore Latin American tech talent with United States companies.
Role Overview
The Senior Back-End/MLOps Engineer - Real-Estate position involves joining a marketplace team to construct backend services and machine learning operations infrastructure. Responsibilities include deploying models, managing feature stores, and supporting real-time data flows. The role bridges product engineering and data science to scale search, ranking, and matching features.
Key Responsibilities
Requirements
Nice to Have
Skills and Tools
Salary and Benefits
About the Company
Truelogic operates as a nearshore staff augmentation provider headquartered in New York with over twenty years of experience delivering technology solutions. The organization employs more than 600 technology professionals across Latin America who collaborate with United States startups and enterprise clients.
How to Apply
Apply on the official company careers page.
Skills and tech stack
Questions candidates ask
What is the primary focus of this role?
The role focuses on building backend systems for search, ranking, and matching while supporting MLOps infrastructure like model deployments and feature stores.
What programming languages are required?
Candidates must be proficient in at least one of Go, Python, Ruby, or JavaScript/TypeScript.
How many years of experience are needed?
Applicants need 5 or more years of professional software engineering experience with a strong backend or full-stack background.
Where is the position located?
The position is based in Mexico City with 100 percent remote work flexibility.
What cloud platforms are relevant for the job?
Experience with cloud platforms such as GCP, AWS, or Azure is required, with a preference for GCP.