Machine Learning Engineer

Summary

We are seeking a highly skilled and motivated AI/ML Engineer to join our HLS team. The ideal candidate will have a strong background in artificial intelligence and machine learning, with recent experience in LangGraph, Pydantic, and Agentic AI. You will be responsible for designing, developing, and deploying AI/ML models and systems that drive our healthcare solutions.

Key Responsibilities:

• Design, develop, and implement AI/ML models and algorithms tailored for healthcare applications.

• Collaborate with healthcare professionals and cross-functional teams to integrate AI/ML solutions into clinical workflows and healthcare systems.

• Utilize LangGraph for efficient data processing and model training, focusing on healthcare data.

• Employ Pydantic for data validation and settings management, ensuring compliance with healthcare regulations.

• Leverage Agentic AI to create intelligent agents that enhance patient care and healthcare provider experiences.

• Conduct research and stay up-to-date with the latest advancements in AI/ML technologies and their applications in healthcare.

• Optimize and maintain AI/ML models for performance, scalability, and regulatory compliance.

• Participate in code reviews and ensure best practices in software development.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

• Proven experience as an AI/ML Engineer or similar role, preferably in the healthcare domain.

• Strong proficiency in Python and relevant AI/ML libraries (e.g., TensorFlow, PyTorch).

• Hands-on experience with LangGraph, Pydantic, and Agentic AI.

• Solid understanding of machine learning algorithms, data structures, and healthcare data standards.

• Excellent problem-solving skills and attention to detail.

• Ability to work collaboratively in a team environment.

• Strong communication skills, both written and verbal.

Preferred Qualifications:

• Experience with healthcare data (e.g., EHR, medical imaging) and healthcare regulations (e.g., HIPAA).

• Experience with cloud platforms (e.g., AWS, Azure, Google Cloud).

• Familiarity with DevOps practices and tools.

• Knowledge of natural language processing (NLP) techniques and their applications in healthcare.