Data Machine Learning Engineer

TL;DR

Data Machine Learning Engineer (Data Science ML): Designing, building, and maintaining scalable data pipelines, architectures, and AI-powered BI applications with an accent on LLM-driven solutions, vector databases, and real-time data processing. Focus on developing advanced semantic retrieval workflows, prompt engineering, and managing end-to-end model training and deployment in cloud environments.

Location: Remote within LATAM countries only with in-person verification required.

Company

hirify.global is an American telecommunications company and industry leader in prepaid communication and payment services, listed on the NYSE with over 1300 employees worldwide.

What you will do

• Design, develop, and maintain scalable data pipelines supporting feature stores, model training, and real-time inference.
• Build workflows for semantic data extraction and retrieval using vector databases and RAG architectures.
• Implement analytics and dashboarding solutions delivering AI-backed insights and natural language queries.
• Manage prompt engineering, orchestration flows, and model fine-tuning for conversational AI interfaces.
• Collaborate with data stakeholders to translate requirements into scalable LLM solutions.
• Document data processes, workflows, and model deployment routines comprehensively.

Requirements

• Must be located in LATAM region with in-person verification.
• 8+ years as Data Engineer with 2+ years in MLOps.
• Excellent English communication skills.
• Proficiency in Python, SQL, PLSQL, and experience with big data technologies (Apache Spark, Hadoop, Kafka).
• Experience with vector databases, RAG workflows, and integrating open-source LLM frameworks.
• Familiarity with cloud platforms like AWS or Azure Machine Learning for LLM deployments.

Nice to have

• Experience with DataStax AstraDB, LangChain, LlamaIndex, and prompt engineering.
• Knowledge of Hugging Face Transformers, LLaMA-4, and MLOps CI/CD pipelines.

Culture & Benefits

• Maximum flexibility in choosing work location within LATAM.
• Full-time employment with a leading global telecommunications company.
• Collaborative BI team environment focused on advanced AI and data engineering.

Hiring process

• Interviews and evaluations conducted in English.
• In-person verification required to confirm candidate identity.
• Use of AI tools to assist recruitment, with final decisions made by humans.