Machine Learning Engineer Intern

Career Guide

A Machine Learning Engineer Intern helps build, test, and improve software that learns from data. Interns typically support experienced engineers by preparing data, training simple models, evaluating results, and shipping small improvements to real products.

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Key Responsibilities

Clean and organize data for training and testing
Build baseline machine learning models under guidance
Evaluate model performance using clear metrics
Write reliable code for data pipelines and model training
Run experiments and track results in a repeatable way
Collaborate with product and engineering teammates to understand requirements
Document work so others can reproduce and review it
Help deploy small model updates into a development environment

Top Skills for Success

Python

Data Cleaning

SQL

Machine Learning Fundamentals

Model Evaluation

Version Control

Testing

Communication

Cloud Basics

Data Privacy Awareness

Career Progression

Can Lead To

Machine Learning Engineer Data Scientist Data Engineer Applied Scientist Software Engineer

Transition Opportunities

Machine Learning Platform Engineer MLOps Engineer

AI Product Engineer

Research Engineer

Machine Learning Technical Lead

Common Skill Gaps

Often Missing Skills

Production CodingModel DeploymentData Pipeline DesignExperiment TrackingPerformance OptimizationMonitoringResponsible AI

Development SuggestionsBuild one end to end project that starts with raw data and ends with a simple deployed model. Add clear tests, track experiments, write concise documentation, and review results with a mentor or peer.

Market Intelligence Report

Machine Learning Engineer Intern is part of the Machine Learning category.Explore our market intelligence report to see how AI and hiring demand are shifting for these roles.

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Salary & Demand

Median Salary Range

Entry LevelUnited States: 25 to 45 USD per hour

Mid LevelUnited States: 45 to 70 USD per hour

Senior LevelUnited States: 70 to 110 USD per hour

Growth Trend

Strong. Demand remains high across tech, finance, healthcare, and retail, with increasing focus on practical model deployment and responsible use.

Companies Hiring

Major Employers

GoogleMicrosoftAmazonMetaAppleNVIDIAIBMSalesforceUberAirbnb

Industry Sectors

TechnologyFinancial ServicesHealthcareRetailManufacturingMedia and EntertainmentTransportationEnergy

Recommended Next Steps

Complete a portfolio project with a public repository and a short readme

Practice SQL and Python with datasets that include missing values and messy inputs

Learn a common machine learning library and implement a baseline model

Add unit tests and basic logging to at least one project

Create a simple model evaluation report with clear metrics and charts

Tailor your resume to highlight impact, not just coursework

Prepare interview stories about debugging, tradeoffs, and teamwork