AI Engineer

Inherent Technologies

Minneapolis (MN)

Remote

USD 120,000 - 190,000

Full time

12 days ago

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Job summary

Inherent Technologies, Inc. is seeking an AI Engineer in Minneapolis with remote options to design and deploy machine learning and generative AI solutions for healthcare-focused use cases.

You will work with Databricks, Python, and Azure ML to build scalable ML pipelines and deliver measurable value. The role requires 3–7+ years of hands-on experience, strong MLOps practices, and the ability to translate product requirements into data-backed model objectives.

Qualifications

  • Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Applied Mathematics, or a related quantitative field.
  • 3-7+ years hands-on experience developing ML/AI models in an applied industry setting.
  • Experience with Azure Databricks and Azure ML is a plus.
  • Strong working knowledge of GitHub Copilot or equivalent AI coding assistant.

Responsibilities

  • Develop ML, DL, and generative AI models to support RCM use cases.
  • Build end-to-end ML pipelines with feature engineering, training, tuning, validation, and monitoring.
  • Research advanced techniques in LLMs, embeddings, retrieval augmentation (RAG), prompt engineering, and document intelligence.
  • Translate requirements into measurable model objectives, data specifications, and evaluation frameworks.
  • Conduct exploratory data analysis to understand data patterns and insights.
  • Implement MLOps practices including versioning, reproducibility, feature stores, and drift monitoring.
  • Collaborate with Data Engineers to ensure feature availability and scalable deployment in Azure Databricks.
  • 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 quantitative field

Tools

Azure Databricks
Azure Machine Learning
Azure Data Lake
Azure Data Factory
Delta Lake
GitHub Copilot

Job description

Position: AI Engineer
Location: Minneapolis, MN *REMOTE *
Duration: 1 Year
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

  • Databricks, Python (pandas, scikit-learn, NumPy, TensorFlow, MLflow) SQL, and Agentic AI frameworks (LangChain, LangGraph, OpenAI, MCP)
  • 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.
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.

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).

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.

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