Operations Research, Engineering Analytics Intern

Job Description:

AI Software Engineers within Operations Research design and develop system wide software solutions applying engineering, mathematical, simulation, machine learning, deep learning and optimization models to drive solutions to complex manufacturing problems. Identify and solve highly complex problems in factory performance, loading, equipment performance, decision science and distribution network problems. Require a thorough understanding of the factory environment and knowledge to develop AI software applications of complex engineering models and apply them to identify and drive solutions. Build, develop, validate and apply mathematically based decision algorithms, heuristics, optimization, simulation models and assist in implementing and tuning models for performance and accuracy. Work closely with the business units to identify root causes, define the strategic and tactical needs and drive the appropriate business and technical software solutions. Develop solutions to problems utilizing formal technical training, business knowledge and engineering judgment. Excellent team, interpersonal, analysis and presentation skills are required to lead and manage projects, and to influence and work within varying levels of customer management and decision bodies.

Qualifications:

You must possess the below minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates. Experience listed below would be obtained through a combination of your schoolwork/classes/research and/or relevant previous job and/or internship experiences.

• Candidate should be in pursuit of a Master's degree in Industrial Engineering or Operations Research with a strong background in software development.
• Expected graduation date of Dec '26 or Summer '27 preferred.

Preferred Qualifications:

• Skilled in Discrete-Event Predictive Modeling and Digital Twin Manufacturing Simulations
• Experienced in Oracle PL/SQL, Python, R, and Applied Statistics
• Strong Analytics and ML experience - Regression, Clustering, Neural networks (feedforward, CNN, RNN, LSTM), Classification, Transformer models and attention mechanisms
• LangChain framework for building LLM applications and agent workflows
• Model fine-tuning techniques (LoRA, QLoRA, full fine-tuning, PEFT)
• Experienced in Data analysis, data visualization, Statistical analysis, Time Series analysis
• Production Planning and Manufacturing Automation experience is a plus
• Optimization CPLEX, Linear and Mixed integer programming is a plus.