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Reyes Coca-Cola Bottling · 2 days ago

Machine Learning Engineer

Niles, IL

Full-time

Hybrid

Mid, Senior Level

$103K/yr - $129K/yr

3+ years exp

Reyes Coca-Cola Bottling is seeking a Machine Learning Engineer to design, build, and maintain CI/CD pipelines for machine learning models. The role involves deploying and managing ML models in production, collaborating with data scientists, and ensuring data security and ethical standards are met.

Food and BeverageManufacturingService Industry

Responsibilities

Design, build, and maintain Continuous Integration/Continuous Development (CI/CD) pipelines for machine learning models

Deploy and manage ML models in production environments using containerization and orchestration technologies

Implement monitoring, logging, and alerting solutions to track model performance, system health, and data drift

Collaborate with data scientists to understand model requirements and optimize the process of transforming models from development to a production-ready state

Create and maintain technical documentation for ML Operations (Ops) processes, infrastructure, and deployments

Define ML/Artificial Intelligence (AI) governance to ensure data security and ethical standards are met for all modeling processes

Travel up to 5% of the time

Other duties as assigned

Qualification

CI/CD pipelinesMachine Learning conceptsPythonCloud platformsSQLBash/shell scriptingInfrastructure-as-CodeData governanceTechnical documentationCollaboration

Required

Bachelor's degree in computer science, Data Science, Mathematics, or related quantitative discipline and 3 to 5 plus years of experience in ML Engineering, Software Engineering, or a related field or High School Diploma/General Education Diploma and 7 plus years of the above stated experience

Preferred

Master's Degree in computer science, Data Science, or other graduate education in related quantitative fields

Hands-on experience with CI/CD pipelines, automation tools, and version control systems like Azure DevOps, Github, or similar and strong understanding of machine learning concepts and the ML development lifecycle

Experience building ML Ops infrastructure and serving models via cloud platforms such as Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP)

Strong proficiency in Python and working knowledge of Bash/shell scripting for automation and system operations

Strong understanding of Structured Query Language (SQL) and experience with big data platforms, i.e., Snowflake, Databricks, or similar

Experience with Infrastructure-as-Code tools, i.e., Terraform, Azure Resource Manager, or similar