Senior Machine Learning Engineer (AI)

TL;DR

Senior Machine Learning Engineer (AI): Building and deploying high-impact ML model pipelines to improve marketing performance and deliver customer value with an accent on robust, performant model architectures and MLOps practices. Focus on leading end-to-end ML pipeline development, optimizing model cost and performance, and ensuring system reliability at scale.

Location: Mexico City

Company

hirify.global is the Customer Company, inspiring the future of business with AI + Data + CRM and pioneering the next frontier of 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 a 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 as well as automating training workflows.

Requirements

• MS or PhD in Computer Science, AI/ML, Software Engineering, or related field.
• 8+ years of experience building and deploying ML model pipelines at scale, with a focus on marketing use cases.
• Expert-level knowledge of AWS services, particularly SageMaker.
• Deep expertise in containerization and workflow orchestration (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 (Snowflake, Spark).
• Experience implementing ML governance policies and ensuring compliance with data security requirements.

Nice to have

• Familiarity with feature engineering and feature store implementations using cloud-native technologies.
• Track record of leading ML initiatives that deliver measurable marketing impact.
• Strong collaboration skills and ability to work effectively with Data Science and Platform Engineering teams.

Culture & Benefits

• Inspiring the future of business with AI + Data + CRM.
• Empowering you to be a Trailblazer, driving your performance and career growth.
• Charting new paths and improving the state of the world through business as a platform for change.