AI/ML Engineering Intern

MasterControl Japan

. Prepare manufacturing records, quality events, and operational data for training and evaluation datasets .

Posted 10/2/2026internshipSalt Lake City • Utah • United StatesEntry Level💰 $30 - $50 per hourWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Proficient in Python programming and familiar with machine learning frameworks such as scikit-learn and PyTorch, with a strong understanding of data manipulation using Pandas and NumPy. Capable of developing predictive models and conducting thorough evaluations while collaborating effectively across technical teams.

Highest-signal resume keywords

Proficiency In PythonFamiliarity With Scikit-LearnExperience With PandasUnderstanding Of Regression And ClassificationFamiliarity With Git

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Python ProgrammingMachine Learning FrameworksData ManipulationPredictive ModelingSQL SkillsFeature EngineeringModel EvaluationVersion ControlTesting CodeData Quality Investigation

Soft Skills

CollaborationDocumentationProblem-SolvingWillingness To Investigate

Tools & Technologies

PandasNumPyScikit-LearnPyTorchGit

Industry Keywords

Data ScienceMachine LearningOperational Risk ScoringQuality OutcomesCo-op Program

Tech Stack

Tools & technologies

NumpyPandasPythonPyTorchScikit-LearnSQL

About the role

Key responsibilities & impact

Prepare manufacturing records, quality events, and operational data for training and evaluation datasets
Investigate data quality, missing values, and relationships between process execution and quality outcomes
Develop and evaluate predictive models for operational risk scoring, batch-outcome prediction, recurring deviations, and nonconformance risk
Experiment with text embeddings, clustering, and retrieval methods for semantic search and quality-event analysis
Develop and test governed language-model applications grounded in computed results and supporting evidence
Create reproducible evaluations, investigate failure cases, document findings, and apply appropriate validation methods
Write and test Python services and APIs
Contribute to training and inference pipelines
Measure reliability, latency, and computational efficiency
Document datasets, features, model configurations, experiments, and evaluation results
Follow practices for version control, testing, customer-data isolation, and secure data handling
Collaborate with data scientists, ML engineers, and platform engineers under technical mentorship

Requirements

What you’ll need

Currently pursuing a degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field
Proficiency in Python
Familiarity with scikit-learn, PyTorch, or a comparable machine learning framework
Experience working with Pandas and NumPy
Basic SQL skills for exploring and preparing data
Understanding of regression, classification, clustering, feature engineering, training and validation splits, overfitting, and model evaluation
Familiarity with Git
Ability to write readable, testable code
Willingness to investigate unexpected results, document findings, and collaborate across disciplines
Currently authorized to work in the United States on a full-time basis
Position intended for students of Northeastern University as part of the Co-op Program, but all applications will be considered

Benefits

Comp & perks

Competitive compensation
Schedule flexibility
Company parties and employee recognition programs
Wellness programs
Professional development and employee skill development
Technical mentorship