- Company Name
- Reyes Coca-Cola Bottling
- Job Title
- Machine Learning Engineer
- Job Description
-
Job Title: Machine Learning Engineer
Role Summary
Design, build, and operate CI/CD pipelines for machine learning models, deploy and manage models in production using containerization and orchestration, monitor and log model performance and system health, maintain ML Ops documentation, and enforce AI governance for data security and ethics.
Expactations
* Deliver reliable, scalable ML deployment pipelines with minimal downtime.
* Maintain continuous monitoring and alerting for model drift, performance decay, and infrastructure health.
* Ensure compliance with data security and ethical standards across all ML processes.
* Communicate model requirements and deployment status with cross‑functional teams.
* Keep documentation current and support audit and certification activities.
Key Responsibilities
* Create and maintain CI/CD workflows for ML model lifecycle.
* Deploy, orchestrate, and scale ML services in cloud or on‑prem environments.
* Set up monitoring dashboards, logs, and automated alerts for models and infra.
* Collaborate with data scientists to translate research models into production‑ready artifacts.
* Document ML Ops processes, infrastructure, and security controls.
* Define and enforce AI governance policies for data usage and model accountability.
* Participate in occasional travel (<5 %) for stakeholder visits or demos.
Required Skills
* Proven experience building ML Ops pipelines using CI/CD tools (Azure DevOps, GitHub Actions, etc.).
* Strong scripting skills in Python; proficiency in Bash/shell for automation.
* Use of containerization (Docker, Kubernetes) and orchestration in production.
* Experience with cloud ML services (Azure ML, AWS SageMaker, GCP AI Platform).
* Familiarity with Infrastructure‑as‑Code (Terraform, ARM, etc.).
* Knowledge of SQL and big‑data platforms (Snowflake, Databricks).
* Ability to monitor, log, and alert on model performance and drift.
* Understanding of ML development lifecycle and best practices.
Required Education & Certifications
* Bachelor’s degree in Computer Science, Data Science, Mathematics, or related quantitative field *or* High School Diploma plus 7 + years of relevant experience.
* 3–5 + years in ML Engineering, Software Engineering, or related roles.
* Master’s degree in a related field preferred.
* Certifications in cloud platforms or DevOps (e.g., Azure, AWS, GCP, Terraform, Kubernetes) are an advantage.