THE ROLE

Our client is looking for a Senior Software Engineer to own and evolve our document data extraction pipeline, used in production by enterprise clients at scale. The system processes PDFs and images, runs OCR, applies ML-based document understanding, and extracts structured fields such as passport numbers, names, and dates.

This role is hands-on and technical. You will design, refactor, and optimise both the ML inference pipelines and the surrounding Python systems, bringing clarity, performance, and robustness.

To be clear on what this is not: not a pure research role, not a junior 'experiment with models' position, and not a GPU-centric ML role. This is a production, systems-level role for someone who knows what breaks in the real world and how to fix it.

WHAT YOU WILL DO

• Own the pipeline. Take ownership of the existing OCR and document understanding pipeline in Python. Evaluate and improve OCR strategy across accuracy, speed and layout fidelity, and rework the labelling and extraction approach to reduce complexity and fragility.





• Optimise inference for production. Make inference fast and reliable in CPU-only environments, tuning for latency, memory and throughput. Introduce production-grade techniques such as ONNX, quantisation and batching, and remove current limitations like token caps, document cropping and brittle heuristics.

• Redesign for scale. Redesign the architecture to support higher volumes across many clients. Make the system easier to reason about, debug, retrain and operate in production. • Grow into broader engineering ownership. Document AI is the dominant focus in year one. Over time the role expands into wider system ownership: backend services that orchestrate document processing, APIs and data pipelines, model lifecycle and versioning, and architecture decisions as usage scales.

WHO WE ARE LOOKING FOR

• Production engineer, not researcher. 6+ years of professional software engineering experience with strong Python in produ

📌 Sr. Software Engineer (Argentina)
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📍 Argentina