Machine Learning Engineer (AI)

TL;DR

Machine Learning Engineer (AI): Supporting the development and deployment of high-impact ML model pipelines to improve marketing performance and deliver customer value. Accent on robust, performant model architectures and MLOps practices. Focus on defining technical ML strategy, owning the ML lifecycle, and leading end-to-end ML pipeline development.

Location: Mexico City

Company

hirify.global is the world's #1 CRM provider, inspiring the future of business with AI + Data + CRM and pioneering enterprise AI with AgentForce.

What you will do

• Define and drive the technical ML strategy with emphasis on robust, performant model architectures and MLOps practices.
• Own the ML lifecycle including model governance, testing standards, and incident response for production ML systems.
• Establish and enforce engineering standards for model deployment, testing, version control, and code quality.
• Implement infrastructure-as-code, CI/CD pipelines, and ML automation with focus on model monitoring and drift detection.
• Design and implement comprehensive monitoring solutions for model performance, data quality, and system health.
• Lead end-to-end ML pipeline development focusing on optimizing model cost and performance.

Requirements

• 5+ years of experience building and deploying ML model pipelines at scale, with focus on marketing use cases.
• Expert-level knowledge of AWS services, particularly SageMaker and related services.
• Deep expertise in containerization and workflow orchestration (e.g., Docker, Apache Airflow) for ML pipeline automation.
• Advanced Python programming with expertise in ML frameworks (TensorFlow, PyTorch) and software engineering best practices.
• Proven experience implementing end-to-end MLOps practices including CI/CD, testing frameworks, and model monitoring.
• Expert in infrastructure-as-code, monitoring solutions, and big data technologies (e.g., Snowflake, Spark).

Culture & Benefits

• Opportunity to make an outsized impact on hirify.global's marketing initiatives.
• Empowerment to drive performance and career growth as a Trailblazer.
• Contribute to continued innovation and industry leadership in CRM and Agentic enterprise space.
• Collaborate closely with Data Science, Data Engineering, Product, and Marketing teams.
• Shape the future of customer engagement through AgentForce AI agents.