Role: AI Engineer - Document Intelligence
Function: Engineering - AI/ML
Location: Remote-first with flexible hybrid options
Type: Full-time
Compensation: Competitive salary with significant equity upside
Industry: AI, Logistics, Financial Technology
About Company
A Y Combinator S24 startup rebuilding freight finance from the ground up. The company automates back-office accounting for freight brokers using freight-native AI agents.
Their AI processes complex accounting paperwork in seconds, not hours. Founded by leaders from Google, Georgia Tech, and Progressive with deep AI and enterprise experience.
Position Overview
You'll design and build intelligent agents that automate document-based freight workflows, directly impacting how the company processes millions of freight documents. You'll architect core perception systems that extract structured insights from messy, real-world documents and create AI agents for seamless email communications. Working closely with experienced founders, you'll have significant ownership over the AI stack and help scale operations up to 10x without increasing headcount.
Role & Responsibilities
- You create accurate and reliable systems to extract and analyze knowledge from scanned, handwritten, and distorted freight documents
- You architect, implement, and deploy AI agents for email and phone communications between freight accounting parties using LLMs and VLMs
- You design and refine high-impact prompts, templates, and evaluation harnesses to ensure robust, reliable agent behavior
- You build scalable pipelines for preprocessing, training, inference, and feedback loops including VLM integration
- You monitor and diagnose agent performance in production, rapidly addressing failures and refining models
- You create and maintain high-quality training, evaluation, and test datasets for document intelligence workflows
- You collaborate with product and engineering teams to integrate AI outputs into production-ready automation solutions
Must Have Criteria
- 2+ years of hands-on ML/AI experience, preferably in document AI or computer vision
- Deep learning expertise with PyTorch or TensorFlow for model development and training
- Proven experience crafting precise prompts for VLMs and LLMs, translating complex tasks into actionable instructions
- Hands-on experience with OCR, visual transformers, and multimodal model architectures
- Experience fine-tuning vision-language models for document understanding tasks
- Proven track record of training and deploying ML models to production environments
- Strong problem-solving mindset with ability to prototype and iterate quickly in ambiguous environments
Nice to Have
- Experience with AWS, Azure, or GCP-based ML infrastructure and deployment
- Knowledge of document layout understanding models (Donut, LayoutLM, PubLayNet)
- Background in conversational AI, voice AI, or NLP research
- Experience with RAG pipelines, foundation models, or vector search systems
- Prior startup experience in fast-paced, high-ownership environments
What We Offer
- Competitive salary with significant equity upside as an early-stage Y Combinator company
- High ownership and zero bureaucracy - help shape the AI stack from day one
- Work on impactful real-world problems that blend AI and automation at massive scale
- Remote-first culture with flexible hybrid options
- Direct collaboration with experienced founders from Google, Georgia Tech, and Progressive
