Sr Machine Learning / AI Engineer - Remote
NAVA Software solutions is looking for a Senior Machine Learning / AI Engineer
Details:
Senior Machine Learning / AI Engineer
Location: Remote
Duration: 1+ year
About the Project
The team has developed an intelligent search solution that includes mobile integration. The next phase focuses on extending member benefits and provider search capabilities to enable greater self-service, while leveraging AI to support intentional prompting and member decision-making.
The selected candidate will play a key role in enhancing AI-driven features, integrating advanced models, and strengthening the data and deployment pipeline across multiple platforms and channels.
Summary of Duties & Responsibilities
• Design, develop, and implement AI/ML models and frameworks to enhance member experience and decision-making.
• Extend intelligent search functionalities with advanced natural language and retrieval capabilities.
• Build and manage ML pipelines connecting platform, AI, and channel teams (DevOps focus).
• Implement Retrieval-Augmented Generation (RAG) and work with Large Language Models (LLMs) for conversational and decision-support systems.
• Apply Model Context Protocols (MCPs) and integrate Knowledge Bases for contextual and dynamic AI responses.
• Collaborate with cross-functional teams to embed AI-driven insights into digital member experiences.
• Serve as a liaison between the enterprise AI team and application/DHP teams to ensure smooth integration.
• Support onboarding, configuration, and integration of new AI components and models.
• Participate in testing, validation, and continuous improvement of deployed AI models and systems.
• Collaborate with data engineering teams to ensure AI models are integrated with data pipelines, data lakes, and enterprise systems.
Required Skills & Qualifications
• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• 3+ years of experience in Machine Learning, Artificial Intelligence, or related software engineering roles.
• Proven experience designing and coding AI/ML solutions end-to-end (Python, PyTorch, TensorFlow, etc.).
• Strong understanding of Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs).
• Experience implementing or utilizing Model Context Protocols (MCPs).
• Understanding of Knowledge Base architecture and integration into enterprise applications.
• Hands-on experience with DevOps practices for ML pipelines and model deployment (CI/CD, containerization, monitoring).
• Experience deploying AI solutions in cloud environments (Azure or AWS preferred).
• Familiarity with data storage, ETL processes, and integration with enterprise data systems.
• Excellent communication and collaboration skills, able to interface between technical and business teams.
Preferred Qualifications
• Experience in healthcare or member services domains.
• Familiarity with intelligent search systems, recommendation engines, or conversational AI.
• Knowledge of data governance, model security, and compliance best practices.
• Experience working in agile environments (Scrum, Kanban).
• Exposure to MLOps practices and cloud data pipelines.
Apply Now
Apply Now
Details:
Senior Machine Learning / AI Engineer
Location: Remote
Duration: 1+ year
About the Project
The team has developed an intelligent search solution that includes mobile integration. The next phase focuses on extending member benefits and provider search capabilities to enable greater self-service, while leveraging AI to support intentional prompting and member decision-making.
The selected candidate will play a key role in enhancing AI-driven features, integrating advanced models, and strengthening the data and deployment pipeline across multiple platforms and channels.
Summary of Duties & Responsibilities
• Design, develop, and implement AI/ML models and frameworks to enhance member experience and decision-making.
• Extend intelligent search functionalities with advanced natural language and retrieval capabilities.
• Build and manage ML pipelines connecting platform, AI, and channel teams (DevOps focus).
• Implement Retrieval-Augmented Generation (RAG) and work with Large Language Models (LLMs) for conversational and decision-support systems.
• Apply Model Context Protocols (MCPs) and integrate Knowledge Bases for contextual and dynamic AI responses.
• Collaborate with cross-functional teams to embed AI-driven insights into digital member experiences.
• Serve as a liaison between the enterprise AI team and application/DHP teams to ensure smooth integration.
• Support onboarding, configuration, and integration of new AI components and models.
• Participate in testing, validation, and continuous improvement of deployed AI models and systems.
• Collaborate with data engineering teams to ensure AI models are integrated with data pipelines, data lakes, and enterprise systems.
Required Skills & Qualifications
• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• 3+ years of experience in Machine Learning, Artificial Intelligence, or related software engineering roles.
• Proven experience designing and coding AI/ML solutions end-to-end (Python, PyTorch, TensorFlow, etc.).
• Strong understanding of Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs).
• Experience implementing or utilizing Model Context Protocols (MCPs).
• Understanding of Knowledge Base architecture and integration into enterprise applications.
• Hands-on experience with DevOps practices for ML pipelines and model deployment (CI/CD, containerization, monitoring).
• Experience deploying AI solutions in cloud environments (Azure or AWS preferred).
• Familiarity with data storage, ETL processes, and integration with enterprise data systems.
• Excellent communication and collaboration skills, able to interface between technical and business teams.
Preferred Qualifications
• Experience in healthcare or member services domains.
• Familiarity with intelligent search systems, recommendation engines, or conversational AI.
• Knowledge of data governance, model security, and compliance best practices.
• Experience working in agile environments (Scrum, Kanban).
• Exposure to MLOps practices and cloud data pipelines.
Apply Now
Apply Now