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# ML Engineer

- **Company:** CORAL AI LLC
- **Location:** New York, NY, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Big Data, Python (Programming Language), Machine Learning, Tensorflow, Pytorch, Deep Learning, Kubernetes, Machine Learning Operations, Docker
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/ml-engineer-new-york-coral-ai-8142877

## About the Role

* 2-5 years of experience in machine learning engineering or research
 * Proven experience in developing and deploying ML solutions for OCR, NLP, document processing, and/or speech/voice technologies
 * Proficiency with Python and ML frameworks like TensorFlow or PyTorch
 * Strong understanding of deep learning architectures (CNNs, RNNs, Transformers, etc.)
 * Experience with cloud platforms (AWS, GCP, or Azure) and scalable model deployment (Docker, Kubernetes)
 * Ability to analyze large datasets, develop metrics, and troubleshoot complex ML pipelines
 * Excellent problem-solving, communication, and teamwork skills
 * Willingness to work on-site in Bengaluru or NYC

Bonus Points

 * Prior experience in healthcare AI, document AI, or voice-based healthcare applications
 * Familiarity with OCR toolkits (Tesseract, AWS Textract, Google Vision API, etc.)
 * Background in productionizing ML models in high-compliance environments

## Description

As an ML Engineer at Coral AI, you will play a critical role in developing and deploying advanced machine learning solutions focused on OCR (Optical Character Recognition), document processing, and voice technologies. You'll collaborate closely with cross-functional teams to architect, train, and optimize state-of-the-art models that power automation and intelligence across our platform., * Design, build, and deploy scalable machine learning models for OCR, document understanding, and voice processing

 * Research and implement algorithms for extracting structured information from unstructured documents and audio
 * Optimize and fine-tune models for real-world performance and reliability
 * Work alongside product, data, and engineering teams to integrate ML solutions into production workflows
 * Analyze model outputs, perform error analysis, and iterate quickly based on results and feedback
 * Document methodologies, experiments, and best practices


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