ML Engineer

Responsibilities

• 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

Requirements

• 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
• Willingness to work on-site in NYC

Preferred Qualifications

• 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

About the Company

Coral AI is engineering the intelligent operating system for a more efficient healthcare industry, tackling administrative bottlenecks through an agentic automation platform that processes complex medical records with high accuracy.