Remote AI Engineer — ML & LLMs for Healthcare RCM

Inherent Technologies, Inc.; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Inherent Technologies, Inc. seeks an AI Engineer to design and deploy ML, DL, and generative AI models for healthcare-related use cases in a remote US setting. You will work with Databricks, Python, and Azure ML to build end-to-end pipelines and ensure production readiness.

You will explore LLMs, RAG, and prompt engineering, while partnering with data engineers to ensure data quality. Strong communication with nontechnical stakeholders is essential for adoption and impact.

Qualifications

• BS or MS in a quantitative field with 3–7+ years of hands-on ML/AI model development.
• Experience building production ML systems; healthcare domain a plus.
• Strong proficiency in Databricks and Python data science stack; knowledge of provider platforms a plus.

Responsibilities

• Develop ML, DL, and generative AI models for RCM use cases.
• Build end-to-end ML pipelines with feature engineering, training, tuning, validation, and monitoring.
• Research LLM techniques, embeddings, RAG, prompt engineering, and document intelligence.
• Translate product requirements into model objectives and evaluation frameworks.
• Conduct EDA to uncover patterns and insights; communicate findings to stakeholders.
• Implement MLOps practices including versioning, feature stores, drift monitoring.
• Collaborate with data engineers to ensure data quality and scalable deployment in Azure Databricks environments.
• Provide cross-functional insights and drive ML adoption across platforms.

Skills

Databricks

Python

pandas

scikit-learn

NumPy

TensorFlow

MLflow

SQL

LangChain

LangGraph

OpenAI

MCP

LLMs

Education

Bachelor's or Master's in Data Science/CS/Statistics

Tools

Azure Databricks

Delta Lake

Azure Machine Learning

Azure Data Lake

Azure Data Factory

Job description

Inherent Technologies, Inc. seeks an AI Engineer to design and deploy ML, DL, and generative AI models for healthcare-related use cases in a remote US setting. You will work with Databricks, Python, and Azure ML to build end-to-end pipelines and ensure production readiness.

You will explore LLMs, RAG, and prompt engineering, while partnering with data engineers to ensure data quality. Strong communication with nontechnical stakeholders is essential for adoption and impact.