Computer Vision Engineer

Responsibilities:

• Design, train, and deploy custom OCR models using Azure Document Intelligence and AWS Textract
• Automate document classification, data extraction from structured and unstructured formats (PDFs, scanned images, invoices, etc.)
• Integrate OCR workflows with Azure Translator for multilingual document processing and AWS Comprehend for NLP-based insights.
• Utilize AWS Bedrock and Azure OpenAI to build GenAI-powered solutions for semantic understanding and summarization of documents
• Apply AWS Rekognition for image-based document analysis and identity verification.
• Develop and maintain scalable pipelines using Python, Java, or .NET for OCR output post-processing (JSON/CSV formats).
• Collaborate with cross-functional teams to gather requirements and deliver tailored solutions.
• Ensure compliance with data privacy, security standards, and cloud governance policies.

Required Skills:

• At least 8 years of experience in OCR technologies and intelligent document processing.
• Proficiency in Azure AI Services, AWS AI/ML stack, and GenAI frameworks.
• Strong programming skills in Python, Java, or .NET.
• Experience with Azure Form Recognizer, AWS Textract, Rekognition and Bedrock.
• Familiarity with EC2,ECS, S3, Lambda, and Step Functions.
• Knowledge of document layout analysis (tables, forms, key-value pairs).
• Experience with NLP tools like AWS Comprehend and translation APIs.
• Understanding of GenAI model training, fine-tuning, and deployment strategies.
• Exposure to Consumer, Retail and Logistics domain document workflows would be an added advantage.
• Familiarity with Terraform, DevOps pipelines, and CI/CD practices is an additional benefit.
• Experience in CI/CD pipelines & Git for code management
• Ability to quickly learn and develop expertise in existing highly complex applications and architectures
• Comfortable working in Agile projects
• Clear and precise communication skills (mandatory since it's a client facing role)
• Strong problem-solving, attention to details is important.
• Bachelor's degree in computer science, information technology, or a similar field (preferable)