Machine Learning Engineer

Walmart de México y Centroamérica; Ciudad de México; Presencial; MXN 600,000 - 800,000; Jornada completa

Descripción de la vacante

Walmart Mexico & Central America is seeking a Machine Learning Engineer (MLOps) to lead the deployment and monitoring of machine learning models in production environments. The role focuses on ensuring scalability through automation, while collaborating with multidisciplinary teams. Candidates should hold a relevant Bachelor's degree and possess at least 3 years of experience in MLOps.

Formación

• Minimum of 3 years working on deployment and operation of machine learning models.
• Proven experience in at least one end-to-end machine learning model deployment project.
• Advanced English required.

Responsabilidades

• Deploy machine learning models into production environments.
• Implement automated pipelines for training, validation, and deployment.
• Continuously monitor model performance to detect drift.

Conocimientos

Python

Docker

SQL

Spark

MLFlow

TensorFlow

PyTorch

Kubeflow

Educación

Bachelor's degree or Engineering in Data Science, Computer Science, Statistics, Applied Mathematics, Artificial Intelligence

Descripción del empleo

Walmart Mexico & Central America is seeking a Machine Learning Engineer (MLOps)

At Walmart Mexico & Central America, we are committed to digital transformation to deliver smarter, more efficient, and scalable experiences. We are looking for a Machine Learning Engineer (MLOps) to join our team and lead the deployment and monitoring of machine learning models in production environments, applying automation, standardization, and technical collaboration best practices.

To implement and maintain machine learning models in production by applying MLOps methodologies and continuous automation flows (CI/CD), while working closely with multidisciplinary teams locally and internationally.

Key Responsibilities

• Deploy machine learning models into production environments, ensuring scalability and performance.
• Implement automated pipelines for training, validation, and deployment of models.
• Continuously monitor model performance to detect drift or degradation.
• Collaborate with data scientists, architects, and developers to integrate models into existing systems.
• Optimize models by tuning hyperparameters and improving accuracy.
• Design scalable data processing solutions that enable reuse and efficiency.

Required Profile

Education: Bachelor's degree or Engineering in Data Science, Computer Science, Statistics, Applied Mathematics, Artificial Intelligence, or a related field.

Experience: Minimum of 3 year working on the deployment and operation of machine learning models in production environments.

Mandatory: Proven experience in at least one end-to-end machine learning model deployment project, fully automated with no manual intervention.

Technical Skills:

• Languages and tools: Python, Docker, SQL, Spark, MLFlow, TensorFlow, PyTorch, Kubeflow
• CI/CD principles applied to machine learning workflows
• Best practices in MLOps and version control for models
• Language: Advanced English is required for effective collaboration with international teams.

We seek individuals who live our values, focus on the customer, embrace change with accountability, and foster a collaborative, inclusive, and high-performance environment.

Interested in joining us?