AI/ML Engineer

Shrive Technologies LLC; Texas; On-site; USD 150,000 - 210,000; Full time

Job summary

Shrive Technologies LLC in Texas seeks an AI Engineer to develop ML, DL, and generative AI models for RCM use cases such as claim outcome prediction and denials classification. You will build end-to-end ML pipelines, perform EDA, and apply advanced techniques in LLMs and RAG.

Collaboration with data engineers will drive deployment on Azure Databricks and related platforms. You will translate requirements into measurable objectives, collaborate with stakeholders, and communicate findings to

Qualifications

• Degree in a quantitative field (BS/MS) required.
• 3–7+ years of ML/AI model development in an applied industry setting (healthcare experience preferred).
• Strong proficiency in Databricks and Python (pandas, scikit-learn, NumPy, TensorFlow, MLflow) and SQL.
• Healthcare familiarity with RCM, including 837/835 transactions, preferred.
• Ability to prototype rapidly in a fast-paced environment and drive iterative delivery.
• Experience with Azure cloud ecosystem (Azure Databricks, ML, Data Lake, Data Factory).
• Hands-on experience with Agentic AI / LLMs / RAG and production ML systems.
• Strong communication to explain technical results to nontechnical stakeholders.

Responsibilities

• Develop ML, DL, and generative AI models to support RCM use cases such as claim outcomes, denials classification, and action recommendations.
• Build end-to-end ML pipelines including feature engineering, model training, hyperparameter tuning, validation, and monitoring.
• Research and apply advanced techniques in LLMs, embeddings, retrieval augmentation (RAG), and document intelligence.
• Translate product requirements into measurable model objectives, data specs, and evaluation frameworks.
• Perform EDA to understand data patterns, anomalies, and business insights.
• Implement MLOps practices: versioning, reproducibility, feature stores, and drift monitoring.
• Collaborate with Data Engineers to ensure data quality and scalable deployment on Azure Databricks and enterprise platforms.
• Communicate insights and model results to cross-functional teams and drive adoption.

Skills

Databricks

Python

pandas

scikit-learn

NumPy

TensorFlow

MLflow

SQL

LangChain

LangGraph

OpenAI

MCP

Education

Bachelor's or Master's in Data Science, Computer Science, Statistics, Applied Mathematics, or related field

Tools

Azure Databricks

Azure Machine Learning

Azure Data Lake

Azure Data Factory

Delta Lake

GitHub Copilot

Job description

Key Responsibilities

For the AI Engineer, required skillset are: Databricks, Python (pandas, scikit-learn, NumPy, TensorFlow, MLflow) SQL, and Agentic AI frameworks (LangChain, LangGraph, OpenAI, MCP) Responsibilities Develop machine learning, deep learning, and generative AI models to support RCM use cases such as claim outcome prediction, denials classification, next best action recommendation, clinical appeal summarization, and workflow optimization. Build end to end ML pipelines including feature engineering, model training, hyperparameter tuning, validation, and monitoring. Research and apply advanced techniques in LLMs, embeddings, retrieval augmentation (RAG), prompt engineering, and document intelligence. Translate operational and product requirements into measurable model objectives, data specifications, and evaluation frameworks. Conduct exploratory data analysis (EDA) to understand data patterns, anomalies, and business insights. Implement and follow best practices around MLOps, including model versioning, reproducibility, feature stores, and drift monitoring. Partner with Data Engineers to ensure feature availability, data quality, and scalable ML/AI deployment within Azure Databricks and enterprise platforms. Collaborate with cross-functional teams to communicate insights, present model results, and drive adoption of ML solutions. Maintain awareness of emerging AI technologies and propose enhancements or new opportunities for Provider Engineering platforms.

Required Qualifications

Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Applied Mathematics, or a related quantitative field.

3 7+ years of hands-on experience developing ML or AI models in an applied industry setting (healthcare experience strongly preferred).

Strong proficiency in: Databricks Python (pandas, scikit-learn, NumPy, TensorFlow, MLflow) SQL

Preferred: Knowledge of US healthcare, ideally with Revenue Cycle Management (RCM) experience, including familiarity with EDI transactions such as 837 and 835.

Ability to thrive in a fast-paced environment with rapid prototyping, ambiguity, and iterative delivery.

Required: Strong working knowledge of GitHub Copilot (or equivalent enterprise-approved AI coding assistant) to accelerate development.

Self-motivated and solution-oriented; able to independently research, troubleshoot, and identify paths forward when facing technical or data challenges.

Experience working in Azure or similar cloud environments: Azure Databricks (MLflow, Delta Lake) Azure Machine Learning Azure Data Lake / Azure Data Factory (in partnership with Data Engineering)

Hands-on experience in at least one of the following: Classification, regression, time series, or recommendation systems Agentic AI / Large Language Models (LLMs) / RAG

Strong statistical modeling foundation and experience building production-quality ML systems.

Ability to communicate technical findings to nontechnical stakeholders clearly and effectively