Senior AI/ML Engineer

Company: WellRithms

Location: Remote (Remote)

Salary: $160,000 - $175,000 a year

Type: Full-time

Remote: Yes

Posted: 2026-08-27

About this role

OUR IDEAL CANDIDATE
We are looking for a Senior AI/ML Engineer who wants to leverage cutting-edge Artificial Intelligence, including Generative AI, LLMs, and modern Agentic frameworks—to fix a broken healthcare system. The ideal candidate possesses a strong foundation in production machine learning, deep experience with cloud-native GenAI architectures (specifically on AWS), and a proven track record of working with sensitive healthcare data. You thrive in a high-impact, collaborative environment where you will design and deploy scalable AI-driven solutions that automate complex billing workflows, detect fraud, extract insights from unstructured claims, and power our next generation of AI products.

RESPONSIBILITIES

  • Design, build, and orchestrate Machine Learning, GenAI, and Agentic AI applications leveraging foundational models (via AWS Bedrock, SageMaker) for automated billing, cost prediction, and document intelligence.
  • Design and build production-grade scalable Machine Learning (ML) pipelines integrating Object Character Recognition (OCR), Natural Language Processing (NLP), Retrieval-Augmented Generation (RAG), and agentic decision-making workflows to process complex medical claims and unstructured data.
  • Establish end-to-end MLOps standards, automated model testing, and robust CI/CD pipelines for automated build, test, and release cycles of both ML models and AI services.
  • Define, provision, and maintain secure cloud environments for AI/ML services using Infrastructure as Code (IaC) tools such as AWS CDK or Terraform.
  • Develop APIs and microservices to enable seamless integration of ML/AI models into existing business applications.
  • Collaborate with cross-functional teams (product, technology, operations, etc.) to align AI solutions with business goals.
  • Implement techniques to improve transparency in AI decision-making, ensuring traceability and model explainability.
  • Ensure compliance with healthcare data regulations (e.g., HIPAA, HITRUST...

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