Machine Learning Engineer

Role Summary Technical resource on the TME product team, partnering with a Project Manager. Builds and maintains data extraction and processing pipelines that transform EU tariff measures data (customs duties, tariffs, VAT, excise taxes) from government sources into structured, client-ready formats. Works using AI-assisted development tools and the BMAD methodology. This is a senior-level position requiring independent architecture and delivery decisions. What You Will Do - Develop AI native applications that extract and process trade compliance data from central EU and member state government sources - both structured (XML, JSON, CSV, HTML tables, APIs) and unstructured (PDF documents, legal text, prose regulations, scanned publications) - Design and build AI native data pipelines that monitor, detect changes, extract, normalise, validate, and release tariff measures data to clients - Integrate AI/LLM capabilities into extraction workflows - using large language models for document understanding, entity extraction, classification, and data structuring - Design and maintain data models for customs duties, VAT/excise information, and tariff measure metadata - Ensure data quality through automated testing, benchmarking against official sources, data source and legal source comparison, and data validation pipelines Required Technical Skills - 3+ years of professional software development - Proficiency in at least two programming languages - e.g., Python, JavaScript/TypeScript, Java, Go, C#, Rust, Kotlin, or similar. We value strong fundamentals over specific language experience - Methodology / Framework: Bmad Method - Data extraction and processing - web scraping, document parsing, API integration, ETL/ELT pipelines. Must be comfortable with both: structured data: XML, JSON, CSV, HTML tables, databases, REST/SOAP APIs; unstructured data: PDFs, legal text, prose regulations, HTML without clear structure, scanned documents - Database design and querying - relatio