ML Engineer - New York

Coral AI•New York City, NY

1d•Onsite

About The Position

At Coral AI, we’re engineering the intelligent operating system for a more efficient healthcare industry. As recently featured in Forbes, we are tackling a massive administrative bottleneck, a $450 billion crisis that consumes 25% of U.S. healthcare spending and forces patients to wait weeks for life-saving treatment. Our agentic automation platform is uniquely designed for healthcare’s "messy" reality, utilising sophisticated AI to digest handwritten faxes, complex medical records, and blurry scans with an unprecedented 98.7% accuracy. Backed by Lightspeed and founded by a team with deep roots in AI and robotics, we’ve scaled to multi-million dollars in ARR in less than six months by delivering immediate, Day-1 value to medical equipment providers, clinics and specialty pharmacies. By slashing patient wait times from five days to under three hours, we’re doing more than just automating paperwork; we’re returning time to clinicians and ensuring that care is never delayed by a document. If you’re a high-ownership builder who wants to solve mission-critical problems in OCR and NLP while making a tangible impact on human lives, come help us build the infrastructure that lets healthcare scale.

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
Excellent problem-solving, communication, and teamwork skills
Willingness to work on-site in Bengaluru or NYC

Nice To Haves

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

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