About the Role
This role involves developing and maintaining backend systems that power document intelligence using machine learning and artificial intelligence. The engineer will work on scalable solutions to extract, classify, and process complex document data.
Responsibilities
- Design and implement backend services for document analysis platforms
- Develop machine learning pipelines to process unstructured text and forms
- Optimize data processing workflows for speed and accuracy
- Collaborate with data scientists to integrate AI models into production systems
- Ensure system reliability and performance under high-volume workloads
- Write clean, maintainable, and well-tested code
- Troubleshoot and resolve issues in distributed systems
- Participate in architectural design and technical decision-making
- Support deployment and monitoring of ML-powered services
- Work with cross-functional teams to define product requirements
- Maintain security and compliance standards for data handling
- Improve model inference efficiency in production environments
- Contribute to API design for internal and external integrations
- Evaluate new technologies for document AI capabilities
- Document system designs and technical specifications
Nice to Have
- Master’s degree in Computer Science, Machine Learning, or related field
- Experience with natural language processing (NLP) applications
- Hands-on work with transformer-based models for text extraction
- Background in building document intelligence or forms-processing systems
- Knowledge of Apache Kafka or similar message queuing systems
- Experience with MLOps tools and practices
- Contributions to open-source AI/ML projects
Compensation
Competitive salary and benefits package
Work Arrangement
Remote position with flexibility for work hours
Team
Collaborative engineering team focused on AI-driven document processing solutions
Why This Role Matters
This position plays a key role in advancing automated document understanding, reducing manual effort, and improving accuracy across critical business processes.
Technology Stack
The team uses Python, TensorFlow, PyTorch, Docker, Kubernetes, and cloud-based AI services to build and deploy document intelligence solutions.
No visa sponsorship available for this role
