We are seeking a skilled AI Engineer with 2 to 3 years of experience in Image Recognition, Natural Language Processing (NLP), Large Language Models (LLMs), and Document Classification and Data Extraction through OCRs combined with object detection techniques. You will play a key role in deploying AI automation agents capable of processing various types of documents, including but not limited to:
- Document Classification
- Document Validation
- Document Editing
- Information Extraction
This is a hands-on role where you will collaborate closely with a multidisciplinary team, including AI engineers, OCR developers, and software developers, to develop intelligent systems that streamline the visa application process.
Key Responsibilities
AI Development and Deployment
- Develop and fine-tune machine learning models, innovate to find time and cost optimized LLM, CLIP, LayoutLM, etc. based solutions for document classification, validation, and information extraction.
- Implement image recognition systems to process scanned or digital copies of documents to develop features like auto-crop, auto-orient, auto-size documents.
- Leverage NLP and LLMs to extract and validate data from structured and unstructured text.
- Leverage and innovate OCR techniques to extract relevant information from different documents by using tools like Tesseract, EAST Text Detector, AWS Textract.
- Utilize object detection techniques like SSD, CNN, YOLO, and other models to enhance build solutions that can handle any new document type and process it accordingly.
- Combine object detection outputs with LLMs to deploy zero-shot or few-shot models effectively.
System Integration
- Integrate AI models with the broader platform for seamless end-to-end processing.
- Work with backend engineers to ensure efficient communication between AI components and other microservices.
- Collaborate with OCR developers to improve the accuracy and performance of text extraction systems.
Optimization and Innovation
- Focus on optimizing strategies to keep the solution cost-effective while ensuring lapse time is minimal.
- Innovate and combine techniques to meet the dual KPIs of cost and time efficiency.
- Research and propose approaches to improve the accuracy, speed, and scalability of AI models.
- Troubleshoot and resolve issues related to AI model performance or integration.
Data Pipeline Management
- Design and maintain data pipelines to preprocess, clean, and structure training datasets.
- Optimize the storage and retrieval of large datasets for machine learning workflows.
Requirements
Technical Skills
- Machine Learning Expertise: Proficiency in training and deploying machine learning models for image and text processing.
- Image Recognition: Hands-on experience with frameworks like OpenCV, TensorFlow, or PyTorch for image-based analysis.
- NLP and LLMs: Familiarity with transformers, NLP libraries (e.g., Hugging Face, SpaCy), and fine-tuning large language models like LLAMA or GPT.
- Object Detection Techniques: Experience with models like SSD, Faster R-CNN, or similar real-time systems to optimize speed and efficiency.
- Programming Skills: Proficiency in Python and familiarity with AI/ML frameworks (e.g., PyTorch, TensorFlow, or Keras).
- Cloud Platforms: Experience deploying models on cloud platforms like AWS, GCP, or Azure.
Experience
- 2-3 years of experience in AI/ML engineering roles with a focus on document processing or related domains.
- Proven track record of building and deploying AI models in production environments.
- Familiarity with handling sensitive and secure data in compliance with data privacy standards.
