Senior Data and ML Engineer

About the role

We are looking for a senior technical leader to own and architect core data infrastructure for a high-impact AI-driven platform. This role focuses on building production-grade extraction and processing systems that transform messy, unstructured documents and communications into clean, structured data assets. You will design foundational systems from the ground up and drive continuous improvements in accuracy and scalability.

Responsibilities

• Own end-to-end data extraction pipelines, converting unstructured inputs (e.g., emails, PDFs, specifications, and supporting documents) into validated, structured datasets.
• Architect and evolve the core data model and infrastructure that unifies entities such as suppliers, documents, requests, pricing, and certifications.
• Design and implement new data processing modules that integrate into an event-driven pipeline.
• Build evaluation frameworks, regression testing, and monitoring to drive extraction accuracy above 85%+ while systematically addressing edge cases.
• Identify opportunities to enhance data granularity, aggregation, and quality to support downstream product features.
• Collaborate closely with product, sales, and customer teams to align the data layer with real business needs and priorities.
• Leverage ML models, agents, and automation to scale extraction processes efficiently rather than relying on manual effort.

Requirements

• 7+ years of experience building production data systems, with a strong track record of architecting and owning data infrastructure from scratch at early-stage or growth companies.
• Demonstrated ability to design broad system architecture and end-to-end pipelines, not just incremental features.
• Deep expertise working with complex, messy, unstructured data sources and turning them into reliable structured outputs.
• Experience treating extraction challenges as ML problems - including building eval sets, performance tracking, and iterative improvements.
• Proficiency in data modeling, pipeline orchestration, and integrating with modern backend systems (e.g., Node/TypeScript environments).

Bonus

• Background in document extraction, NLP, ML pipelines, or supply chain/procurement-related domains