MLOps Engineer (AWS) (México Only)

MLOps Engineer (AWS)

About DaCodes

We are a high-impact software and digital transformation expert firm. Over 10 years, we have created technology and innovation-focused solutions thanks to our team of nearly 300 talented #DaCoders, including developers, architects, UX/UI designers, PMs, QA testers and more. Our team collaborates on projects with clients in LATAM and the United States, achieving outstanding results.

At DaCodes, you will have the opportunity to drive your professional development, work on diverse projects across different industries, and contribute to the design, implementation and optimization of cloud infrastructures. Our DaCoders have a major impact on the success of our business and our clients'. You will be the expert participating in our projects and will have access to disruptive startups and global brands.

About the Role

We are looking for an MLOps Engineer (AWS) to join a project focused on a demand forecasting platform and schedule optimization operating in production on AWS.

The selected person will be responsible for ensuring stability, reliability and scalability of existing pipelines, actively participating in deployments, monitoring, automation and continuous improvement of the platform. This role is oriented toward operation and maintenance of Machine Learning solutions in production, rather than developing models from scratch.

We are looking for someone with solid experience in Python, AWS cloud services, deployment automation and good software engineering practices, capable of working on existing code, optimizing processes and ensuring operational continuity of systems.

Responsibilities

• Operate and maintain the demand forecasting and schedule optimization platform in production.
• Ensure that ML pipelines run reliably on AWS, identifying and resolving incidents proactively.
• Manage deployments of models and services using Docker, CI/CD and IaC tools (SAM / CloudFormation).
• Refactor and improve existing Python code to increase performance, maintainability and test coverage.
• Monitor services and pipelines via CloudWatch and equivalent tools.
• Collaborate with the data science team to integrate new model versions into the production environment.
• Participate in code reviews (PRs) following Git and pytest best practices.
• Document configurations, infrastructure decisions and operational procedures.

Required Technical Stack

• Python 3.12 (solid): pandas, Polars, numpy, scikit-learn, XGBoost; ability to refactor external code.
• AWS: Lambda, S3, IAM, CloudWatch, Step Functions, SageMaker, ECR.
• Docker: build and debug of images.
• CI/CD: Azure DevOps or equivalent (GitHub Actions / GitLab CI).
• IaC: reading and editing of SAM / CloudFormation.
• Git + pytest: branch work, PRs and unit tests.

Desirable Skills (Nice to Have)

• Glue, EventBridge, MLflow.
• Multiprocessing in Python.
• OR-Tools / CP-SAT (constraint optimization) — can be trained.
• Snowflake, DevSecOps.

Requirements

• 3–5 years of experience in MLOps, DevOps or ML infrastructure roles.
• Demonstrable experience maintaining ML pipelines in production on AWS.
• Proactive profile with ability to work autonomously.
• Modality: Hybrid CDMX.

Benefits

• 🚀 Integration with global brands and disruptive startups.
• 🏡 Remote work / Home office.
• 📍 If hybrid or in-person modality is required, you will be informed in the first session.
• ⏳ Schedule adjusted to the assigned work cell / project.
• 📅 Monday to Friday work.
• 🎉 Day off on your birthday.
• 🏥 Major medical expense insurance (applies for Mexico).
• 🛡️ Life insurance (applies for Mexico).
• 🌎 Multicultural work teams.
• 🎓 Access to courses and certifications.
• 📢 Meetups with special guests from the IT field.
• 📡 Virtual integration events and interest groups.
• 📢 English classes.
• 🏆 Opportunities within our different business lines.
• 🏅 Proudly certified as Great Place to Work.