Senior AI/ML Engineer — Remote, Drive Customer Insights

Medallia; Candelaria; Remote; MXN 600,000 - 1,200,000; Full time

Job summary

NTT DATA seeks a Sr AI/ML Engineer (Remote) to join our team in Mexico. The role focuses on developing scalable ML solutions to enhance customer intelligence and guide business decisions.

You will work with cross-functional teams to deploy models that optimize marketing investments and customer engagement, using Python, PySpark, SQL, and relevant ML frameworks in a distributed data environment.

Qualifications

• Bachelor's degree in data science, CS, engineering, mathematics, statistics or related quantitative field.
• 2-4 years of professional ML or data engineering experience.
• Proficiency in Python and SQL; PySpark or similar big data tools as a plus.
• Familiarity with TensorFlow or PyTorch.

Responsibilities

• Develop and implement ML models such as recommendation engines, customer segmentation, and predictive analytics.
• Collaborate with data scientists and engineers to translate business requirements into technical solutions.
• Write clean, production-grade Python, PySpark, and SQL code.
• Build and maintain data pipelines and workflows using Spark, Airflow or similar tools.
• Participate in model validation, testing, and deployment processes.
• Communicate findings and model insights to technical and non-technical stakeholders.
• Work in an agile environment with product managers, data scientists, and engineers.

Skills

Machine learning

Data engineering

Python

SQL

Big data tools

Cloud platforms

Education

Bachelor's degree in quantitative field

Tools

Python

PySpark

TensorFlow

PyTorch

AWS Sagemaker

Databricks

Job description

NTT DATA seeks a Sr AI/ML Engineer (Remote) to join our team in Mexico. The role focuses on developing scalable ML solutions to enhance customer intelligence and guide business decisions.

You will work with cross-functional teams to deploy models that optimize marketing investments and customer engagement, using Python, PySpark, SQL, and relevant ML frameworks in a distributed data environment.