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Coral AI

ML Engineer - New York

New York CityfulltimemidAdded 1 month ago

About this role

Coral AI seeks an ML Engineer to develop advanced machine learning solutions for OCR, document processing, and voice technologies that automate healthcare administrative workflows. You'll design and deploy scalable models that help clinicians access critical patient information faster, directly reducing wait times and improving care delivery.

What you'll do

  • Design, build, and deploy scalable ML 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
  • Integrate ML solutions into production workflows alongside product and engineering teams
  • Perform error analysis and iterate based on model outputs and feedback
  • Document methodologies, experiments, and best practices

What they're looking for

  • Machine learning engineering (2–5 years experience)
  • Python and ML frameworks (TensorFlow or PyTorch)
  • Deep learning architectures (CNNs, RNNs, Transformers)
  • OCR, NLP, document processing, and/or speech/voice technologies
  • Cloud platforms (AWS, GCP, or Azure)
  • Model deployment (Docker, Kubernetes)
  • Large dataset analysis and ML pipeline troubleshooting
  • Problem-solving and communication

Benefits

  • Work on mission-critical healthcare problems impacting millions
  • Collaborative, high-growth environment with expert team
  • Competitive salary and comprehensive benefits
  • Modern office in Bengaluru or NYC with on-site flexibility
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Coral AI

Coral AI builds AI-powered healthcare automation software that processes medical documents and streamlines administrative workflows to improve patient care timelines. The company is hiring Backend Engineers and ML Engineers to develop scalable platform infrastructure and machine learning solutions for OCR, document processing, and voice technologies.

View all jobs at Coral AI

Likely interview questions

  • Walk us through a specific OCR or document processing project you've built—what was your approach to handling messy, real-world data like handwritten text or poor-quality scans?
  • How have you approached optimizing ML models for production deployment, especially when balancing accuracy with latency and cost constraints?
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