Senior ML Engineer - Remote, Production & Data Pipelines

Spin; San Luis Potosí; Presencial; MXN 550.000 - 900.000; Jornada completa

Descripción de la vacante

NTT DATA in Guadalajara, Jalisco (MX) is seeking a Sr AI ML Engineer (Remote) to join our data science and engineering teams. You will build scalable ML models to support marketing decisions and customer engagement.

Collaborate with data scientists to translate requirements into production Python, SQL, and PySpark code. Contribute to data pipelines with Spark and Airflow and participate in validation, testing, and deployment in an agile environment.

Formación

• Bachelor's degree in a quantitative field.
• 2-4 years of ML or data engineering experience.
• Strong Python and SQL skills.
• Experience with PySpark or big-data tools.
• Experience with TensorFlow or PyTorch.
• Familiarity with cloud ML tools (AWS SageMaker, Databricks).
• Strong collaboration and communication skills.

Responsabilidades

• Develop and deploy ML models like recommender systems and segmentation.
• Collaborate with data scientists and engineers to translate requirements.
• Write production-quality Python, PySpark, and SQL code.
• Build and maintain data pipelines with Spark and Airflow.
• Participate in model validation, testing, and deployment.
• Communicate insights to technical and non-technical stakeholders.
• Work in an agile environment with cross-functional teams.

Conocimientos

Python

SQL

PySpark

ML frameworks (TensorFlow/PyTorch)

Cloud platforms (AWS SageMaker/Databri

Data pipelines

Team collaboration

Educación

Bachelor's degree in a quantitative field

Herramientas

Airflow

Spark

Descripción del empleo

NTT DATA in Guadalajara, Jalisco (MX) is seeking a Sr AI ML Engineer (Remote) to join our data science and engineering teams. You will build scalable ML models to support marketing decisions and customer engagement.

Collaborate with data scientists to translate requirements into production Python, SQL, and PySpark code. Contribute to data pipelines with Spark and Airflow and participate in validation, testing, and deployment in an agile environment.