Senior Data/Machine Learning Engineer Job Title: Senior Data/Machine Learning Engineer Location: Bogotá, Colombia Founded in 1990, IDT Corporation is a telecommunications company headquartered in New Jersey. Today, it is an industry leader in prepaid communication and payment services. We are seeking a skilled Data/ML Engineer to join our Business Intelligence team and take an active role in designing, building, and maintaining the end-to-end data pipeline, architecture, and design that powers our warehouse, LLM-driven applications, and AI-based Business Intelligence. Responsibilities: - Design, develop, and maintain scalable data pipelines to support ingestion, transformation, and delivery into centralized feature stores, model-training workflows, and real-time inference services. - Build and optimize workflows for extracting, storing, and retrieving semantic representations of unstructured data to enable advanced search and retrieval patterns. - Architect and implement lightweight analytics and dashboarding solutions that deliver natural language query experience and AI-backed insights. - Define and execute processes for managing prompt engineering techniques, orchestration flows, and model fine-tuning routines to power conversational interfaces. - Oversee vector data stores and develop efficient indexing methodologies to support retrieval-augmented generation (RAG) workflows. - Partner with data stakeholders to gather requirements for language-model initiatives and translate into scalable solutions. - Create and maintain comprehensive documentation for all data processes, workflows, and model deployment routines. Requirements: - 8+ years of experience as a Data Engineer with 2+ years focused on MLOps. - Excellent English communication skills. - Effective oral and written communication skills with the BI team and user community. - Demonstrated experience in utilizing Python for data engineering tasks, including transformation, advanced data manipulation, and large-scale data processing. - Deep understanding of vector databases and RAG architectures, and how they drive semantic retrieval workflows. - Skilled at integrating open-source LLM frameworks into data engineering workflows for end-to-end model training, customization, and scalable inference. - Experience with cloud platforms like AWS or Azure Machine Learning for managed LLM deployments. - Hands-on experience with big data technologies including Apache Spark, Hadoop, and Kafka for distributed processing and real-time data ingestion. - Experience designing complex data pipelines extracting data from RDBMS, JSON, API, and Flat file sources. - Demonstrated skills in SQL and PLSQL programming, with advanced mastery in Business Intelligence and data warehouse methodologies, along with hands-on experience in one or more relational database systems and cloud-based database services. - Understanding of software engineering principles and skills working on Unix/Linux/Windows Operating systems, and experience with Agile methodologies. - Proficiency in version control systems, with experience in managing code repositories, branching, merging, and collaborating within a distributed development environment.