Data/ML Engineer

IDT is a communications and financial services company founded in 1990 and headquartered in New Jersey, US. Today it is an industry leader in prepaid communication and payment services and one of the world's largest international voice carriers. We are listed on the NYSE, employ over 1700 people across 20+ countries, and have revenues in excess of $1.5 billion.

We are looking for a skilled Data/ML Engineer to join our BI 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 BI.

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

• Data and ML Engineer with a proven 5+ year history of building scalable infrastructure.
• Excellent English communication skills.
• 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.

Pluses

• Experience with vector databases such as DataStax AstraDB, and developing LLM-powered applications using popular open source frameworks like LangChain and LlamaIndex, including prompt engineering, retrieval-augmented generation (RAG), and orchestration of intelligent workflows.
• Familiarity with evaluating and integrating open-source LLM frameworks such as Hugging Face Transformers/LLaMA-4 across end-to-end workflows, including fine-tuning and inference optimization.
• Knowledge of MLOps tooling and CI/CD pipelines to manage model versioning and automated deployments.

What we offer

• Remote work opportunity.
• B2B Employment or full-time employment option.
• Stable job with long-term growth perspective.
• Competitive salary with annual performance review.
• Continuous learning and career growth opportunities.