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Software Engineering Intern
- Collaborate with experienced engineers on real-world software projects
- Contribute to the design, development, and testing of innovative solutions
- Work with modern tools and technologies in a supportive team environment
- Currently pursuing a BS in Computer Science (or related field)
- Hands-on experience with one or more: Python, C++, Java, or MATLAB
- Strong problem-solving skills and a willingness to learn
- Ability to work well in a team setting
- Work on meaningful, technically challenging projects
- Learn from a team passionate about engineering excellence
- Gain real-world experience in a collaborative and innovative environment
- Build next-generation solutions to help tackle complex issues.
- Engage in end-to-end software engineering processes.
- Be part of high-caliber teams of engineers focused on designing, creating, and fine-tuning simulation platforms that assess and validate the latest algorithms and systems for autonomy.
- Contribute to multidisciplinary teams, and actively participate in software design evaluations, code reviews, and test strategy planning.
- Computer Science / Information Technology
- Artificial Intelligence (AI)
- Data Science
- Data Analysis
- Natural Language Processing
- Automation Testing (i.e. Selenium)
- Are working towards a Bachelor of Science in Computer Science, Computer Engineering, or a related technical field.
- Have classroom experience in or knowledge of software design patterns in either C++, Python, Java, or MATLAB.
- Have a minimum 3.0 GPA on a 4.0 Scale. Note: When prompted to upload attachments, please include a copy of your college transcripts (unofficial transcripts are acceptable).
- Have pursued technical projects and extracurricular activities outside of the classroom. Specifically, AI project experience.
- Possess classroom or related experience in working closely with autonomous systems and machine learning algorithms.
- Have classroom or professional experience in developing with middleware or containerization software tools, such as Data Distribution Service, ZeroMQ, Docker, or Kubernetes.
- Hold classroom experience in data science and statistical analysis.
- Have experience in a modern software development environment, such as Agile or Kanban, that includes automated testing (Selenium), continuous integration and deployment, and DevSecOps protocols.