Data Software Engineer / MLOps / MLE

Job description

We welcome a Data Software Engineer / MLOps / MLE to become part of our team and contribute to enabling multi-country operations for the LATAM region.

A candidate with a strong foundation in Python, Spark, and PySpark, along with hands-on experience in AWS and Databricks, will thrive in this role.

Responsibilities

- Design data pipelines that scale efficiently using Python, Spark, and PySpark

- Construct AWS infrastructure and manage deployments through Databricks

- Establish CI/CD workflows for machine learning models with Jenkins and similar platforms

- Apply Amazon SageMaker to construct, train, and release machine learning models

- Track model performance and drive improvements in efficiency

- Uphold standards for data quality and integrity at every stage

- Engage with teams across functions to generate innovative use cases

- Develop unit tests covering all phases of machine learning processes

- Modify data science pipelines to align with project demands

- Exchange information clearly to resolve questions and address technical matters

Requirements

- Knowledge of Python, Spark, and PySpark

- Background in AWS and Databricks

- Expertise in MLOps methodologies and tools including Jenkins

- Skills in using Amazon SageMaker for machine learning lifecycle management

- Experience with CI/CD platforms and Terraform for infrastructure automation

- Flexibility to approach new use cases with ease

- Understanding of principles behind production-ready data science pipelines

- Background in preparing data and building models

- Competency in designing unit tests for each step of machine learning workflows

- Ability to communicate ideas and technical details effectively

Nice to have

- Familiarity with Apache Airflow

- Knowledge of practices that ensure high data quality

- Certification in Databricks

- Certification in Jenkins