Senior Machine Learning Engineer

Summary

Join a growing team building intelligent automation tools for the healthcare industry as a fully remote Machine Learning Backend Engineer. Leverage AI and backend engineering to streamline complex workflows. This role requires strong experience in backend development, ML model integration, and web automation. You will design, develop, and maintain backend systems using Python, Django, and RESTful APIs. The ideal candidate will have experience with machine learning pipelines, AI-powered solutions for document processing, and web automation using Selenium/Python. You will collaborate with frontend engineers and ensure the performance, scalability, and reliability of backend services.

Requirements

• 5+ years of full-stack development experience, with a focus on backend engineering
• Strong proficiency in Python , Django , and React
• Experience implementing and deploying machine learning models in production
• Proficiency in NLP , OCR , and working with LLMs (e.g., GPT)
• Experience with Selenium/Python for web automation
• Solid understanding of PostgreSQL , WebSocket , and AWS Lambda
• Experience with Docker , LocalStack , and container-based development
• Strong knowledge of version control using Git
• Excellent problem-solving, analytical, and communication skills
• Experience in Agile development environments
• Self-starter mindset with the ability to work independently in a distributed team

Responsibilities

• Design, develop, and maintain backend systems using Python, Django , and RESTful APIs
• Build and optimize machine learning pipelines for healthcare data processing and automation
• Develop AI-powered solutions for document processing , OCR , and data extraction from structured and unstructured sources
• Implement web automation using Selenium/Python to interact with third-party portals and services
• Collaborate with frontend engineers using React/Vue to deliver full-stack solutions
• Ensure performance, scalability, and reliability of backend services
• Deploy and maintain ML models in production environments
• Work with PostgreSQL , WebSockets , and AWS Lambda for data storage and processing
• Apply prompt engineering techniques to fine-tune and optimize large language models (LLMs)
• Participate in Agile ceremonies, conduct code reviews, write tests, and maintain documentation

Preferred Qualifications

Familiarity with EDI healthcare formats (837, 835, 270/271)

Benefits

• Fully remote, flexible work environment
• Work on real-world AI applications in the healthcare space
• Join a forward-thinking team solving complex automation challenges
• Continuous learning and professional growth opportunities