AI & Data Science Graduate Intern

The AI & Data Science Graduate Intern will assist in developing data-driven solutions, machine learning and AI models, and analytics platforms that support sensor technology development and engineering decision-making. The intern will work closely with multidisciplinary teams across Systems, MEMS, Optics, Electronics, Software, Manufacturing, and Product Development to help transform engineering data into actionable insights and support technology innovation.

Tasks & Responsibilities

• Assist in designing and developing data analytics and machine learning solutions to support engineering, testing, and product development activities.

• Support the development of predictive models and statistical analyses to help improve product performance, yield, and reliability.

• Contribute to building and maintaining automated dashboards and visualization tools that provide insights into technology and operational performance.

• Help develop and maintain data processing pipelines and analytical scripts that ensure data quality, integrity, and accessibility.

• Participate in automating engineering workflows, including testing, characterization, performance analysis, and reporting activities.

• Apply foundational machine learning, computer vision, and advanced analytics techniques to help solve engineering challenges.

• Analyze engineering and manufacturing data to identify trends, root causes, and optimization opportunities.

• Collaborate with cross-functional teams to understand technical needs and help translate them into analytical and automation solutions.

• Support the development of intelligent testing platforms and machine-learning-based decision support tools.

• Research and evaluate emerging data science and AI technologies to contribute to team innovation initiatives.

• Prepare technical reports, dashboards, and documentation to communicate project findings to team members.

• Actively participate in knowledge sharing, embrace mentorship, and adopt data science best practices across the organization.

Requirements

• Recently graduated with a Bachelor's or Master's degree in Computer Science, Computer Engineering, Data Science, Artificial Intelligence, Mathematics, or a related discipline.

• Academic, internship, or project-based experience in Data Science, Machine Learning, Artificial Intelligence, or Analytics.

• Solid foundational understanding of machine learning algorithms, statistical analysis, predictive modeling, and data analytics techniques.

• Familiarity with building basic data pipelines, analytical scripts, or automated reporting solutions.

• Proficiency in Python and standard data science frameworks; familiarity with MATLAB, Octave, or similar analytical tools is preferred.

• Familiarity with Large Language Models (LLMs), Generative AI concepts, and foundational AI models, with an interest in applying them to engineering, scientific data, or automation use cases.

• Basic experience with SQL databases, data management, and visualization platforms.

• Knowledge of computer vision, image processing, signal processing, or DSP techniques is considered a strong advantage.

• Exposure to cloud-based environments and modern data engineering practices is a plus.

• A strong interest in supporting engineering, manufacturing, semiconductor, sensor technology, or scientific research environments.

• Strong analytical, problem-solving, and communication skills, coupled with a proactive willingness to learn.