We are seeking senior data engineers interested in developing a document intelligence service for professional workers, collaborating with our global RD, PM, and growth teams. The service leverages AI to assist professional workers in automating the processing of business documents. For instance, it can automatically scan professional documents, including contracts, financial documents, and medical records, and then extract relevant data for workflow automation.

Responsibilities

1. Research and evaluate pioneering machine learning and statistical models
2. Use machine learning and analytical techniques to build prediction models for document intelligence solutions.
3. Design, develop, and test advanced models for predictive user behaviors
4. Design efficient, scalable, automated processes for large scale data analyses, model development, model validation, and model implementation
5. Collaborate across engineering teams to provide solutions using machine learning techniques
6. Collaborate with project managers to create new features leveraging the benefits of machine learning techniques

Minimum qualifications

1. Master degree in Computer Science, related technical field, or equivalent practical experience
2. At least five years of relevant experience in NLP (natural-language processing)
3. Experience with one general-purpose programming language (e.g., Python, Java, C/C++)
4. Experience in algorithms and libraries of NLP
5. Experience in data processing of textual and numerical data
   
6. Familiar with Linux/Unix environments and containers
7. Superb attention to detail, logical thinking, working independently and responsive to multiple challenges in a fast-moving team environment

Preferred qualifications

1. Advanced degree in engineering or technical/scientific field of study
2. Familiar with attention-based transformers NLP models and algorithms
3. Experience with RAG and multi-modal LLM fine-tuning
4. Experience with generative AI for document processing applications
5. Experience in building and operating large scale distributed systems or applications
6. Excellent documentation, communication, organizational, and analytical skills
7. Experience in MLOps