Job Information
IBM DevOps Engineer (Machine Learning) in GUADALAJARA, Mexico
Introduction
We are looking for an experienced DevOps Engineer with strong cloud security and AWS expertise to support the deployment of Data and Machine Learning solutions. The ideal candidate will have hands‑on experience automating cloud workflows, building CI/CD pipelines, and ensuring secure, scalable, and reliable deployments of ML models and data services. This role requires strong AWS proficiency, excellent debugging capabilities, and the ability to collaborate effectively with cross‑functional teams.
Your role and responsibilities
· Deploy Data solutions and Machine Learning models in AWS using Lambda functions, Batch Jobs, and ECS.
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Build, optimize, and maintain CI/CD pipelines using GitHub Actions and Git.
Implement and manage cloud infrastructure using AWS CloudFormation (Infrastructure as Code).
Monitor, troubleshoot, and optimize cloud-based systems to ensure high availability, reliability, and performance.
Automate operational workflows across AWS services such as Lambda, ECR, ECS, Fargate, IAM, EventBridge, VPC, and CloudWatch.
Ensure security best practices are applied across deployments, access configurations, and cloud infrastructure.
Collaborate with data scientists, ML engineers, and software development teams to support end‑to‑end model deployment workflows.
Diagnose and resolve issues in cloud-based environments, ensuring minimal downtime and smooth release processes.
Required technical and professional expertise
5+ years of experience in cloud security, DevOps, or a related field.
Strong hands-on experience with GitHub Actions and Git.
Advanced proficiency in AWS services, including:
o ECR, ECS, IAM, EventBridge, VPC, CloudWatch
Deep understanding of DevOps principles such as CI/CD, automation, infrastructure scalability, and monitoring.
Strong problem‑solving skills with the ability to debug and troubleshoot cloud‑based systems.
Excellent communication and collaboration skills, with experience working on cross-functional teams.
Experience with Infrastructure as Code, preferably AWS CloudFormation.
Preferred technical and professional experience
Experience deploying machine learning models or data pipelines in AWS.
Familiarity with container orchestration and optimization in ECS/Fargate.
Understanding of ML workflows, model versioning, or data engineering concepts.
Knowledge of additional DevOps tools (e.g., Terraform, Kubernetes, Docker).
Experience optimizing cost, security, and performance in cloud environments.
IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.