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описание
FieldFlo is a mobile-first SaaS platform serving the construction, demolition, and environmental services industries. It supports compliance, safety, time tracking, training, and field operations for teams across the U.S.
задачи
Design and deploy document understanding pipelines for PDFs, drawings, forms, and other unstructured documents
Train and optimize models such as Donut, LayoutLM, and TrOCR, or similar document AI architectures
Build multi-stage AI workflows combining OCR, computer vision, and LLM-based reasoning
Develop object detection and extraction models to identify regions of interest, annotations, tables, labels, and document elements
Convert extracted information into structured outputs with confidence scoring and traceability
Build evaluation frameworks, monitoring, and retraining workflows
Collaborate with engineering and product teams to ship AI features into production
требования
3+ Years of professional ML Engineering experience
Production experience with Document Understanding solutions
Hands-on experience training or deploying models such as Donut, LayoutLM, TrOCR, OCR/document extraction architectures, or equivalent multimodal document AI models
Experience building end-to-end document processing pipelines, including OCR, information extraction, document classification, structured data extraction, and LLM-based document workflows
Strong Python skills and experience with PyTorch, Transformers, OpenCV, and the Hugging Face ecosystem
Experience with AWS, Azure, or GCP
Docker and containerized deployment experience
Strong English communication skills
Будет плюсом: experience with architectural drawings, engineering plans, construction documents, or technical schematics; annotation tools such as CVAT, Label Studio, and Roboflow; agentic AI or multi-step LLM pipelines; PDF rendering, OCR engines, coordinate systems, and document processing frameworks; startup or SaaS experience
условия
B2B contract
Paid national holidays based on the candidate’s country
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