Machine Learning Platform Engineer (AI)

TL;DR

Machine Learning Platform Engineer (AI): Building and scaling core infrastructure, platform services, and CI/CD pipelines for ML initiatives with an accent on AI-native tooling and developer velocity. Focus on designing autonomous agents for workflow acceleration, implementing MCP servers, and optimizing cloud infrastructure on AWS.

Location: Mexico City, Mexico

Company

hirify.global is a global leader in CRM and cloud software, integrating AI across its marketing, sales, and service verticals.

What you will do

• Develop AI-native engineering tools and autonomous agents to automate CI diagnosis, infrastructure ops, and developer onboarding.
• Design and manage secure, scalable AWS infrastructure (EKS, S3, SageMaker, Lambda) using Terraform.
• Build and maintain core ML platform components, including Model Registry and project permission services.
• Optimize CI/CD pipelines via GitHub Actions and ArgoCD, integrating AI-powered self-healing and documentation.
• Curate an internal AI tool marketplace and build self-service CLI/Web tools for ML engineers and data scientists.
• Implement monitoring, reliability solutions (Grafana, PagerDuty), and ensure security compliance for AI tool integrations.

Requirements

• 9+ years of experience as a Platform, Software, or ML Infrastructure Engineer.
• Proven practice in AI-native engineering using tools like Claude Code or Cursor in daily workflows.
• Strong software engineering skills in Python and deep expertise in AWS.
• Extensive experience with Terraform, Docker, Kubernetes, GitHub Actions, and ArgoCD.
• Hands-on experience with MLOps concepts, Model Context Protocol (MCP) servers, and agent evaluation.
• Must be based in Mexico City, Mexico.

Nice to have

• Experience within the hirify.global ecosystem.
• Knowledge of agent memory patterns (context management, long-term retrieval) and RAG pipelines.
• Experience with vector/graph databases and modern data platforms like Snowflake, Kafka, or Flink.
• Experience with Feature Stores (e.g., Feast) and A/B testing platforms.
• Knowledge of Airflow or similar workflow orchestration tools.

Culture & Benefits

• AI-first engineering culture where AI is used as a force multiplier for productivity.
• Environment that encourages experimentation, out-of-the-box thinking, and rapid shipping.
• Opportunity to impact critical organizational growth verticals in marketing, sales, and service.
• Focus on developer velocity and the creation of reusable internal tool marketplaces.