AI/ML Cloud Architect - Remote

Are you ready to shape the future of data-driven solutions for the insurance and healthcare industries? Our client is a leader in advanced analytics and machine learning, is looking for a highly skilled AI/ML Cloud Architect to join their team and drive innovation in risk assessment and underwriting.

They specialize in leveraging advanced analytics and machine learning to unlock the power of data. By analyzing prescription histories, medical records, and other health data, they help insurers make smarter, faster decisions. Their cutting-edge tools simplify and automate the underwriting process, using predictive modeling and data integration to revolutionize the insurance space.

The Role

As an AI/ML Cloud Architect, you will be pivotal in building the infrastructure to support large-scale machine learning models. Your work will directly impact how healthcare data—like EHRs, OCR data, and other documentation—is processed, analyzed, and integrated for use by insurance providers. You’ll develop robust, scalable systems to handle complex datasets and ensure seamless operations across the company's platforms.

Key Responsibilities

• Architect and implement scalable data infrastructures for AI/ML applications.
• Leverage OCR and LLM (Large Language Model) capabilities to process and analyze healthcare documentation, including faxed and billed data.
• Integrate EHR (Electronic Health Records) with machine learning pipelines to create actionable insights for insurers.
• Collaborate with data scientists, engineers, and product teams to design and deploy machine learning solutions at scale.
• Optimize data workflows and support the development of industry-leading predictive models.

What They Are Looking For

• Experience:
• 10+ years of experience developing high-quality software.
• 5+ years of experience in AI/ML development, with a strong understanding of cloud infrastructure.

• Technical Expertise:
• Proven expertise with OCR technologies and LLMs.
• Experience integrating and analyzing EHR data for healthcare or insurance applications.
• Proficiency in cloud platforms (AWS, Azure, or GCP) and scalable architecture.
• Deep understanding of machine learning pipelines and data engineering.