AI/ML Engineering Intern

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Описание

About MasterControl: MasterControl Inc. is a leading provider of cloud-based quality and compliance software for life sciences and other regulated industries. Our mission is the same as that of our customers to bring life-changing products to more people sooner. The MasterControl Platform helps organizations digitize, automate and connect quality and compliance processes across the regulated product development life cycle. Over 1,000 companies worldwide rely on MasterControl solutions to achieve new levels of operational excellence across product development, clinical trials, regulatory affairs, quality management, supply chain, manufacturing and postmarket surveillance. For more information, visit [link] Summary MasterControl is looking for a Machine Learning Intern to help build AI capabilities for life-sciences quality and manufacturing. Our AI/ML platform combines predictive machine learning, self-hosted language models, and governed analytical workflows to help customers identify quality risks, investigate deviations, and understand manufacturing performance. You will work alongside data scientists, ML engineers, and platform engineers on real manufacturing execution records and quality-event data. This internship offers hands-on experience across data preparation, model development, evaluation, and production integration, with projects scoped to your experience and supported by technical mentorship. Key Responsibilities • Prepare data and develop features. Help transform manufacturing records, quality events, and related operational data into reliable training and evaluation datasets. Investigate data quality, missing values, and relationships between process execution and quality outcomes. • Build and evaluate predictive models. Contribute to models for operational risk scoring, early batch-outcome prediction, recurring deviations, and nonconformance risk. Compare simple statistical and machine learning baselines with more advanced approaches. • Support semantic search and quality-event analysis. Experiment with text embeddings, clustering, and retrieval methods to identify similar deviations, organize unstructured information, and improve access to relevant evidence. • Contribute to governed language-model applications. Help develop and test capabilities that interpret user questions, connect them to approved analytical procedures, and produce responses grounded in computed results and supporting evidence. • Run rigorous experiments. Create reproducible evaluations, investigate failure cases, and document findings. Apply appropriate validation methods, prevent data leakage, and assess performance beyond overall accuracy, including false positives, calibration, and prediction lead time where relevant. • Help integrate models into production. 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. • Maintain reproducibility and traceability. Document datasets, features, model configurations, experiments, and evaluation results. Follow team practices for version control, testing, customer-data isolation, and secure data handling. Qualifications • Education: Currently pursuing a degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field. • Programming: Proficiency in Python and familiarity with scikit-learn, PyTorch, or a comparable machine learning framework. • Data skills: Experience working with Pandas and NumPy, along with basic SQL skills for exploring and preparing data. • Machine learning fundamentals: Understanding of regression, classification, clustering, feature engineering, training and validation splits, overfitting, and model evaluation. • Engineering and collaboration: Familiarity with Git; an ability to write readable, testable code; and a willingness to investigate unexpected results, document findings, and collaborate across disciplines. Helpful, but Not Required 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 is also valuable. Prior life-sciences experience is not required. Potential for Full-Time Opportunity High-performing interns may be considered for full-time positions upon graduation. Position intended for students of Northeastern University as part of the Co-op Program, but all applications will be considered. Why Work Here? #WhyWorkAnywhereElse? MasterControl is a place where Exceptional Teams come together to do their best work. In fact, hiring Exceptional Teams is a core value of ours. MasterControl employees are surrounded by intelligent, motivated, and collaborative individuals. We like to call it #TheBestTeamOnThePlanet. We work hard to develop and challenge our employees' skillsets, recognize their contributions, encourage professional development, and offer a one-of-a-kind culture. This is why we say #WhyWorkAnywhereElse? MasterControl could be your next (and last) career move! Here are some of the benefits MasterControl employees enjoy: Competitive compensation Schedule flexibility Company parties and employee recognition programs Wellness programs Much, much more! Applicants must be currently authorized to work in the United States on a full-time basis. The US base hourly range for this full-time position is $30 - $50. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. 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