AI/ML Engineer I: Cloud Analytics & Insights

MiniMed; Minnesota; On-site; USD 71,000 - 121,000; Full time

Benefits offered by this job

Health insurance

401(k) plan with company match

Employee Stock Purchase Plan

Job summary

MiniMed is seeking an AI/Data Science Engineer I to deliver intelligent analytics and AI-powered solutions that turn complex data into actionable insights across the organization. The role blends applied data science with modern AI engineering, requiring Python strength, cloud deployment, and a keen eye for real-world impact.

You will partner with engineers and scientists to build AI apps, deploy ML models to cloud environments, and craft production-grade data models and visualizations for

Qualifications

• Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, or related field.

Responsibilities

• Partner with engineers and scientists to deploy AI-powered applications and pipelines.
• Develop, deploy, and maintain ML models to cloud environments with API serving infrastructure.
• Write production-grade Python and build SQL data models across cloud data warehouses.
• Prototype ML models for predictive analytics use cases.
• Leverage AI-assisted development tools to improve velocity and code quality.
• Communicate findings clearly to both technical and non-technical stakeholders.

Skills

Python

Pandas

NumPy

Data Visualization

scikit-learn

PyTorch

TensorFlow

Cloud Platforms

SQL

Git

Docker

Kubernetes

Education

Bachelor's degree in CS/DS/Engineering

Tools

Snowflake

Databricks

BigQuery

Azure Synapse

SageMaker

Job description

MiniMed is seeking an AI/Data Science Engineer I to deliver intelligent analytics and AI-powered solutions that turn complex data into actionable insights across the organization. The role blends applied data science with modern AI engineering, requiring Python strength, cloud deployment, and a keen eye for real-world impact.

You will partner with engineers and scientists to build AI apps, deploy ML models to cloud environments, and craft production-grade data models and visualizations for