Senior Backend & MLOps Engineer | Remote

Truelogic; Bogotá ciudad; A distancia; COP 372.474.000 - 558.711.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

100% Remote Work

Highly Competitive USD Pay

Paid Time Off

Autonomy in work

Work with U.S. companies

Descripción de la vacante

Truelogic is seeking a Senior Back-End Engineer/MLOps to join a Marketplace team working at the intersection of full-stack product engineering and machine learning operations. You will help build and maintain the backend systems that power search, ranking, and matching experiences, while also supporting ML pipelines, model deployment, feature stores, and real-time data infrastructure.

You'll collaborate closely with data scientists, product partners, and engineers to bring machine learning

Formación

• 5+ years of professional software engineering experience with strong backend or full-stack development.
• Hands-on experience with MLOps or production machine learning systems including Vertex AI, MLflow, Kubeflow, or equivalent.
• Experience with feature stores (e.g., Chalk).
• Strong SQL skills and data/feature pipelines.
• Experience with cloud platforms (GCP, AWS, Azure) and ML deployment.

Responsabilidades

• Build and maintain full-stack features across marketplace products, including search, ranking, and user-facing experiences.
• Develop and support ML Ops infrastructure: model deployment pipelines, feature stores, real-time data pipelines, monitoring.

Conocimientos

Backend development

Go

Python

Ruby

JavaScript/TypeScript

MLOps

ML models deployment

Feature stores

SQL

Cloud (GCP/AWS/Azure)

Data pipelines

Debugging

Communication

Herramientas

Vertex AI

MLflow

Kubeflow

Chalk

Descripción del empleo

Truelogic is seeking a Senior Back-End Engineer/MLOps to join a Marketplace team working at the intersection of full-stack product engineering and machine learning operations. You will help build and maintain the backend systems that power search, ranking, and matching experiences, while also supporting ML pipelines, model deployment, feature stores, and real-time data infrastructure.

You'll collaborate closely with data scientists, product partners, and engineers to bring machine learning