MLOps Engineer

Description

Job Summary: Administration, monitoring, and deployment into production of models developed by the data science team, ensuring their proper performance and code quality. Key Highlights: 1. Monitoring and management of data science models in production 2. Ensures code quality and testing for production code (60% coverage) 3. Implementation of continuous integration and delivery (CI/CD) **Header \- External** ------------------------- Entity: Federal District Location Type: Corporate Tower Diana **BTP Position Objective** ------------------------------- Administration, monitoring, and deployment into production of models developed by the data science team.**Key BTP Responsibilities** ------------------------------------- Monitoring the performance of data science models in production. This is achieved by verifying that periodic model executions run successfully; in case of failure, implementing corrective steps to ensure proper model execution. Additionally, ensures models remain within desired performance metrics, proactively preventing and responding to data drift and concept drift. 20% Ensures all production code achieves a minimum test coverage (60%), that code is properly formatted, and that it has undergone a linting process to correct programming and stylistic errors. This is accomplished by reviewing and approving changes submitted by data scientists, as well as ensuring the working platform supports continuous integration by establishing necessary procedures for automated code review. 20% Conducts lifecycle monitoring of models—including scope, data used, modeling techniques applied, and release to production—using tools such as MLFlow. 20% Ensures continuous delivery (CD) by triggering build, code review, and release activities (where applicable) on the platform used for deploying production model code with every push. 20% Supports model development through creation and improvement of a feature store to store the most useful features for data science models. 20%**Education (Minimum and Preferred)** -------------------------------- Minimum Education: Bachelor’s degree in Computer Science, Systems Engineering, or related field Preferred Education: Master’s degree in Computer Science, Data Science, or related field**Experience (Minimum and Preferred)** ---------------------------------- Minimum Experience: 3 years Preferred Experience: 5 years**Required Licenses/Certifications** ---------------------------------------- Python 90% PySpark 80% Cloud 80% Git 90% SQL 90%**Languages (Speaking, Writing, Reading)** --------------------------------- English 90%**Required Computing Tools** ---------------------------------- Python Spark Git AWS (CodeCommit, CodePipeline, CodeBuild, …) Azure SQL Airflow Docker DevOps Knowledge CI /CD**Footer \- External** ---------------------------- At AT\&T Mexico, we know inclusion strengthens our teams; therefore, we promote equal opportunity without discrimination based on sex, gender, sexual orientation, gender identity or expression, age, disability, socioeconomic status, physical appearance, ethnic origin, skin color, culture, pregnancy, or any other reason. Furthermore, we advance equity by implementing reasonable accommodations within the workplace.