AI/ML Engineer - AWS

- Expertise in OCR frameworks – AWS Textract, Azure Form Recognizer, Google Document AI, or Mistral OCR. - Proficiency in Python and ML frameworks such as PyTorch or TensorFlow. - Experience in developing AI services using FastAPI or Flask.

Job Summary We are seeking an experienced AI/ML Engineer to design and implement intelligent automation solutions using Computer Vision, OCR, Deep Learning, and Vision-Language Models (VLMs). The role involves building proof-of-concepts (PoCs) and scalable AI platforms on AWS, focusing on automation use cases such as waste overflow detection, contamination classification, and contract data extraction. The ideal candidate will combine strong technical expertise with business alignment to deliver measurable process improvements and operational efficiency. Must-Have Skills (Mandatory)

- Strong understanding of CNN architectures such as ResNet, EfficientNet, YOLO, Mask R-CNN, and Vision-Language Models (LLaVA, GPT-4V, etc.). - Expertise in OCR frameworks – AWS Textract, Azure Form Recognizer, Google Document AI, or Mistral OCR. - Proficiency in Python and ML frameworks such as PyTorch or TensorFlow.

- Experience in developing AI services using FastAPI or Flask. - Strong knowledge and hands-on experience with AWS cloud services – S3, Lambda, SageMaker, Step Functions, EC2, Docker, SQS, SNS, and CloudWatch. - Solid understanding of AI evaluation metrics (precision, recall, F1 score, OCR accuracy) for classification and detection models.

Good-to-Have Skills (Optional) - Exposure to Azure AI or Google Cloud AI services. - Experience in developing Cordial AI or Domain-Specific AI models.

- Proficiency in Python and ML frameworks such as PyTorch or TensorFlow. - Experience in developing AI services using FastAPI or Flask. - Strong knowledge and hands-on experience with AWS cloud services – S3, Lambda, SageMaker, Step Functions, EC2, Docker, SQS, SNS, and CloudWatch.

- 5+ years of hands-on experience in AI/ML engineering, specializing in Computer Vision, OCR, and Deep Learning. - Strong understanding of CNN architectures such as ResNet, EfficientNet, YOLO, Mask R-CNN, and Vision-Language Models (LLaVA, GPT-4V, etc.). - Expertise in OCR frameworks – AWS Textract, Azure Form Recognizer, Google Document AI, or Mistral OCR.