FieldFlo

ml engineer for document intelligence

In short

Senior ML Engineer role at FieldFlo, a mobile-first SaaS platform for construction, demolition, and environmental services, focused on building document understanding pipelines (OCR, computer vision, LLM-based reasoning) to process PDFs, drawings, and forms. Requires 3+ years of production ML engineering experience with models like Donut, LayoutLM, or TrOCR, strong Python/PyTorch skills, and cloud experience. Remote B2B contract requiring at least 2 hours of overlap with US Mountain Time.

About FieldFlo
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.
Responsibilities
•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
Requirements
•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
Nice to have
•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
Conditions
•B2B contract
•Paid national holidays based on the candidate's country
•Optional unpaid personal time off
•Three-month probation
•At least 2 hours of overlap with US Mountain Time

Stop applying.
Get referred.

$10 in free credits

In just 60 seconds, fully on autopilot — Eraldt's AI agents read your CV, map the roles you fit, find live vacancies and the people who can refer you, write personal emails, and get you referred.

This isn't an application: your CV doesn't go to the company, and we don't promise a referral for this exact role.

Discover who else lands interviews on autopilot