Founding Applied AI Research Scientist - Jobot : Job Details

Well-Funded Seed Stage Startup in Generative AI & LLM Space / Remote FlexibilityThis Jobot Job is hosted by: Caitlyn HardyAre you a fit? Easy Apply now by clicking the Apply buttonand sending us your resume.Salary: $180,000 - $210,000 per yearA bit about us:We are a well-funded Seed-stage startup that has plans to double our team size in the next 6 months. Our product is public and already generating revenue. This product is unlike anything on the market; it was created for developers building Generative AI applications.Our team is hiring a Founding Applied AI Research Scientist who has experience tackling challenges at the intersection of document understanding, multimodal learning, and cutting-edge AI research. In this role, you will design, train, and evaluate document understanding models for extracting complex data, such as tables, forms, and structured text from documents. You will also develop and optimize multi-modal visual Q&A models, enabling our platform to understand and answer questions based on both textual and visual information.Why join us?

• Excellent medical, dental, and vision benefits
• 401k match
• Meaningful equity
• Unlimited PTO and paid holidays
• Company offsites
• Bonus
• Remote flexibility

Job Details

• 4+ years of experience working with AI/ML models, specifically in the fields of document understanding, computer vision, and multi-modal learning.
• Proven expertise in training and evaluating models for complex document extraction, including structured data like tables and forms.
• Deep NLP Expertise: Experience with transformer-based models such as BERT, LayoutLM, T5, or DocFormer.
• OCR Integration: Proficiency in integrating OCR technologies for extracting text from scanned documents and PDFs.
• Model Pretraining and Fine-tuning: Experience with pretraining large models and fine-tuning them for document understanding tasks.
• Layout Analysis: Understanding document layout and structure for effective table detection and hierarchy extraction.
• Benchmarking and Evaluation: Experience with document-specific datasets and evaluation techniques.
• Vision-Language Models: Familiarity with models that integrate visual and textual data for document understanding.
• Solid programming skills in Python and proficiency in at least one deep learning framework (e.g., TensorFlow, PyTorch).
• Ph.D. or Bachelor's degree in a quantitative field such as Computer Science, Mathematics, or equivalent industry experience.

Interested in hearing more? Easy Apply now by clicking the Apply button.