Document AI Scientist - ML, OCR & NLP Expert

SAP SE; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Document AI is a product engineering team within SAP Labs Singapore, developing intelligent document processing solutions used by thousands of customers worldwide. You will work with AI scientists and data engineers to build, validate, and deploy models for document understanding and layout analysis.

We seek ML researchers and engineers who can design scalable training pipelines, evaluate model performance, and collaborate across Agile teams to ship impactful features.

Qualifications

• Master's or PhD in Computer Science, Data Science, or a related technical field, or equivalent experience.
• Outstanding Bachelor's degree holders with relevant experience may be considered.
• Fluency in English is required for this role.

Responsibilities

• Design, develop, and validate machine learning models for document extraction, OCR, and layout analysis.
• Build and maintain scalable training pipelines for document processing workflows.
• Collaborate with data engineers on annotated dataset creation and synthetic data strategies.
• Experiment with NLP and computer vision techniques, translating research into product features.
• Optimize models for accuracy and scalability in cloud-based production environments.
• Support model deployment and monitoring alongside engineering teams.

Skills

Machine learning fundamentals

MLOps

Deep learning

Prompt engineering

LLM fine-tuning

Agile/Scrum

English fluent

Education

Master's or Ph.D. in CS/Data Science or related field

Bachelor's degree with relevant experience

Tools

Python

Job description

Document AI is a product engineering team within SAP Labs Singapore, developing intelligent document processing solutions used by thousands of customers worldwide. You will work with AI scientists and data engineers to build, validate, and deploy models for document understanding and layout analysis.

We seek ML researchers and engineers who can design scalable training pipelines, evaluate model performance, and collaborate across Agile teams to ship impactful features.