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MasterControl

QMS and MES software for compliance

AI Engineer Intern

Applied Machine LearningConfirmed live in the last 24 hours
InternshipUnited States$30 - $50 /hrHybrid

About the Job

Requirements

  • Currently pursuing a degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
  • Proficiency in Python and familiarity with scikit-learn, PyTorch, or a comparable machine learning framework.
  • Experience working with Pandas and NumPy, along with 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.
  • Applicants must be currently authorized to work in the United States on a full-time basis.

Responsibilities

  • Prepare manufacturing records, quality events, and related operational data as reliable training and evaluation datasets; investigate data quality, missing values, and relationships between process execution and quality outcomes.
  • Contribute to predictive models for operational risk scoring, early batch-outcome prediction, recurring deviations, and nonconformance risk; compare statistical and machine learning baselines with advanced approaches.
  • Experiment with text embeddings, clustering, and retrieval methods to identify similar deviations, organize unstructured information, and improve access to relevant evidence.
  • Help develop and test language-model capabilities that interpret user questions, connect them to approved analytical procedures, and produce responses grounded in computed results and supporting evidence.
  • Create reproducible evaluations, investigate failure cases, and document findings; apply validation methods, prevent data leakage, and assess false positives, calibration, prediction lead time, and overall accuracy as relevant.
  • Write and test Python services and APIs, contribute to training and inference pipelines, and measure reliability, latency, and computational efficiency under the guidance of ML and platform engineers.
  • Document datasets, features, model configurations, experiments, and evaluation results; follow team practices for version control, testing, customer-data isolation, and secure data handling.

Desired Qualifications

  • Coursework, research, or personal projects involving time-series or sequential data, anomaly detection, imbalanced classification, text embeddings, information retrieval, or open-source language models.
  • Exposure to Docker, Linux, Spark, cloud infrastructure, or model-serving APIs.

About the Company

MasterControl

QMS and MES software for compliance

MasterControl provides software that combines Quality Management System (QMS) and Manufacturing Execution System (MES) tools for regulated industries such as pharmaceuticals, medical devices, and nutraceuticals. The platform helps manage regulatory compliance, quality control, and manufacturing workflows in one place to bring products to market safely and efficiently. It standardizes Good Manufacturing Practice (GxP) processes, handles document management, change control, training, audits, and CAPA, and tracks manufacturing execution through MES features. By focusing on integrated, compliance-driven capabilities and serving a broad base of more than 1,100 customers, it differs from generic software, with the goal of helping regulated manufacturers move products to market faster while maintaining high quality and lower risk.

Company size
501-1,000
Company stage
Series A
Total funding
$150M
Headquarters
Salt Lake City, UT
Founded
1993

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