AI Engineer (Intern)
Role Overview
The AI Engineer (Intern) role is a remote internship focused on supporting the design, development, and testing of AI models and software components used in defense, aerospace, manufacturing, maintenance, and supply chain applications.
Day-to-day tasks may include implementing and evaluating machine learning algorithms, preparing and cleaning datasets, writing and maintaining code for model training and deployment, and assisting in the integration of AI capabilities into existing software systems.
The intern will collaborate with engineers and product team members to document technical work, contribute to experiments and prototypes, and help troubleshoot performance issues.
The role also involves researching emerging AI techniques, summarizing findings, and applying them to practical use cases under guidance.
Key Skills for This Role
Full Job Posting
Company Description
NexCommand AI LLC is a technology company focused on developing advanced AI and enterprise software solutions for defense, aerospace, manufacturing, maintenance, and supply chain operations.
The organization builds tools that help complex industries improve decision-making, efficiency, and reliability.
The company offers opportunities for interns to work on impactful projects that support critical infrastructure and mission-driven environments.
Role Description
The AI Engineer (Intern) role is a remote internship focused on supporting the design, development, and testing of AI models and software components used in defense, aerospace, manufacturing, maintenance, and supply chain applications.
Day-to-day tasks may include implementing and evaluating machine learning algorithms, preparing and cleaning datasets, writing and maintaining code for model training and deployment, and assisting in the integration of AI capabilities into existing software systems.
The intern will collaborate with engineers and product team members to document technical work, contribute to experiments and prototypes, and help troubleshoot performance issues.
The role also involves researching emerging AI techniques, summarizing findings, and applying them to practical use cases under guidance.
Qualifications
- Foundational skills in programming and software development (e.g., Python, Java, or similar languages) and familiarity with version control tools.
- Basic knowledge of machine learning or AI concepts (such as supervised learning, neural networks, or data preprocessing) and interest in applied AI for industrial or defense-related contexts.
- Ability to work with data (collecting, cleaning, organizing, and interpreting datasets) and use common data analysis or visualization tools.
- Strong problem-solving abilities, attention to detail, and capacity to document and communicate technical findings clearly.
- Comfort working in a remote environment, managing time effectively, and collaborating through digital communication tools.
- Enrollment in or recent completion of a degree program in Computer Science, Engineering, Data Science, Mathematics, or a related field is preferred.
- Interest or coursework in areas such as aerospace, defense, manufacturing, logistics, or operations research is a plus.
- Eligibility to work on projects that may relate to sensitive or regulated industries, as required by applicable laws and company policies.
- Must be currently enrolled in an ABET Accredited University in an engineering program.
Internship Details
- Internship Duration: 3 Months.
- This internship does not lead to an employment position.
Work Location
- Work Location: Remote.
Responsibilities
- Implement and evaluate machine learning algorithms.
- Prepare and clean datasets.
- Write and maintain code for model training and deployment.
- Assist in the integration of AI capabilities into existing software systems.
- Collaborate with engineers and product team members to document technical work.
- Contribute to experiments and prototypes.
- Help troubleshoot performance issues.
- Research emerging AI techniques, summarize findings, and apply them to practical use cases under guidance.
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