Senior JavaFX Engineer

2 days ago


Kottayam, India Invito Staffing Solutions Full time

The missionBuild a desktop JavaFX application that lets non-technical users drop in invoices (PDF/image) and export clean CSVdata. Invoices come in all shapes—your job is to make the app read them like a human: robust parsing, confidence scoring, and easy validation.What you’ll buildJavaFX desktop app (Java 17+) with a clean, responsive UIInvoice ingestion: PDF, PNG/JPG, multi-page, batches, drag-and-dropAI/OCR pipeline (choose best fit; hybrid is fine):Classical OCR (e.g., Tesseract) + layout analysis orCloud OCR (e.g., AWS Textract, Google Vision) orLLM-assisted parsing (prompting/JSON schema) with guardrailsField extraction (line-items + headers): vendor, invoice #, dates, currency, taxes, subtotals/totals, PO, line descriptions, qty, unit price, amountsValidation & review UI: highlight zones, flag low-confidence fields, quick fixes, autocompleteCSV export: stable schema, locale/number/date normalizationRules & heuristics: vendor templates, regex fallbacks, learned patternsQuality metrics: confidence scores, per-field accuracy, reject reasons, simple analyticsOperate offline where possible with optional cloud connectorsYou’re a great fit if you have4+ years Java; 2+ years JavaFX building production desktop appsReal-world OCR/NLP or document understanding experience (invoices, receipts, forms)Hands-on with one or more: Tesseract, Textract, Google Vision, Azure Form Recognizer, OpenCV, spaCy, LLM JSON extractionComfortable designing parsing pipelines: pre-processing, layout detection, table extraction, post-processing, and human-in-the-loop reviewStrong data wrangling: CSV schemas, date/currency parsing, edge casesSolid testing: golden files, fixture PDFs, deterministic pipelinesNice to havePrompt engineering for structured outputs with LLMsVendor-specific templateing and auto-learningExperience with Maven/Gradle, native packaging, code signingKnowledge of ONNX/TensorFlow Lite models for document layoutBasic DevOps for OCR services and model hostingTech we expect to use (flexible)Java 17+, JavaFX, Gradle, Tesseract/OpenCV or Textract/Vision, optional Python micro-services for ML bits, SQLite for local cache, JUnit + test fixtures, GitHub Actions CI.Success looks like≥95% header-field accuracy on a mixed test set≥90% line-item recall on clear tabular invoicesReview UI fixes a typical invoice in 


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