ML Engineer

CodeRound; Hinoba-an; On-site; PHP 600,000 - 1,100,000; Full time

Job summary

Automate Healthcare is seeking an ML Engineer to design, train, and deploy OCR, document processing, and voice-enabled ML solutions. You will collaborate with product and data teams to build scalable pipelines and production-grade models.

The role emphasizes model deployment, data pipelines, REST APIs, and cloud infrastructure, with a focus on MLOps, fine-tuning LLMs, and prompt engineering to automate healthcare workflows.

Qualifications

• Experience with ML/DL workflows for OCR and document understanding.
• Production-ready ML model deployment and monitoring experience.
• Familiarity with voice processing and data pipelines is required.

Responsibilities

• Design, build, and deploy scalable ML models for OCR, document understanding, and voice processing
• Research and implement algorithms to extract structured data from documents and audio
• Optimize and fine-tune models for real-world performance and reliability
• Collaborate with product, data, and engineering teams to integrate ML solutions into production workflows
• Analyze model outputs, perform error analysis, and iterate based on results and feedback
• Document methodologies, experiments, and best practices

Skills

OCR

Document processing

Voice processing

Machine learning

Deep learning

Model deployment

Backend integration

Data pipelines

REST APIs

MLOps

LLM fine-tuning

Prompt engineering

Cloud infrastructure

Tools

TensorFlow

PyTorch

Docker

Kubernetes

GCP

AWS

Job description

Client: Automate healthcare's administrative work so patients get care faster

Requirements:

Machine learning Deep learning Model deployment Backend integration Data pipelines REST APIs MLOps LLM fine-tuning Prompt engineering Cloud infrastructure

As an ML Engineer, 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.

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

Nice to have:

Machine learning Deep learning Model deployment Backend integration Data pipelines REST APIs MLOps LLM fine-tuning Prompt engineering Cloud infrastructure