Remote AI/ML Engineer for Enterprise ML & LLM Pipelines

Noblesoft Technologies Inc.; United States; Hybrid; USD 140,000 - 200,000; Full time

Benefits offered by this job

Remote work option

Job summary

Noblesoft Technologies Inc. is seeking an AI/ML Engineer in Minneapolis, MN with hybrid remote options. You will develop ML and generative AI models for RCM-related use cases, build end-to-end pipelines, and advance MLOps practices to ensure scalable deployment.

You will collaborate with data engineers, communicate insights to stakeholders, and stay ahead of emerging AI technologies to improve Provider Engineering platforms.

Qualifications

• Bachelor's or Master's in CS, Data Science, Statistics, or related quantitative field.
• 3+ years hands-on ML/AI modeling in industry; healthcare experience preferred.
• Strong coding in Python and SQL with experience in Databricks/Azure.
• Experience with LLMs, RAG, embeddings, and production ML systems is a plus.

Responsibilities

• Develop ML, DL, and generative AI models for healthcare use cases.
• Build end-to-end ML pipelines including feature engineering and deployment.
• Research advanced techniques in LLMs, retrieval augmentation, and prompts.
• Translate requirements into measurable model objectives and data specs.
• Perform EDA to uncover data patterns and insights.
• Implement MLOps practices: versioning, feature stores, drift monitoring.
• Collaborate with Data Engineers to ensure data quality and deployment.
• Communicate results to stakeholders and drive adoption.
• Stay updated on new AI technologies and opportunities for platforms.

Skills

Databricks

Python

SQL

LangChain

LangGraph

OpenAI

MCP

MLflow

TensorFlow

Pandas

NumPy

scikit-learn

MLOps

GitHub Copilot

Azure

Education

Bachelor's or Master's in CS/DS/Stats

Tools

Azure Databricks

Azure ML

Delta Lake

MLflow

Azure Data Factory

Job description

Noblesoft Technologies Inc. is seeking an AI/ML Engineer in Minneapolis, MN with hybrid remote options. You will develop ML and generative AI models for RCM-related use cases, build end-to-end pipelines, and advance MLOps practices to ensure scalable deployment.

You will collaborate with data engineers, communicate insights to stakeholders, and stay ahead of emerging AI technologies to improve Provider Engineering platforms.