Summer 2027 - Product Support Engineering Intern 6470 - 6442
| Verified Pay check_circle | Provided by the employer$37- $97 per hour |
|---|---|
| Hours | Full-time |
| Location | Dallas, TX Dallas, Texas open_in_new |
About this job
Job Description
The Product Support Engineering Intern (Sustainment & Data) position at Shield AI focuses on optimizing the reliability, availability, and maintainability (R&M) of autonomous defense systems. You will develop critical sustainment tools, analyze logistics data, and build data pipelines to track fleet health.
- Current student pursuing a degree in Industrial Engineering, Systems Engineering, Data Science, Aerospace, Mechanical Engineering, or a related STEM field.
- Strong proficiency in Python, SQL, R, or data visualization tools (e.g., Tableau, Power BI).
- Solid understanding of probability, statistics, and engineering economics as applied to reliability and logistics.
- Effective communication skills to translate complex data sets into actionable engineering recommendations.
- Ability to commit to an on-site, 10-week full-time internship program.
- Prior experience or coursework in reliability engineering, logistics engineering, or predictive maintenance.
- Familiarity with database design, data warehousing, or system architecture concepts.
- Knowledge of aerospace or military sustainment standards (e.g., MIL-HDBK-217, MIL-STD-1629).
- Develop Sustainment Tools: Create, maintain, and optimize tools, dashboards, and data pipelines/systems to track fleet metrics and maintenance data.
- Logistics & R&M Engineering: Assist with Reliability, Availability, and Maintainability (R&M) analyses, including Failure Mode, Effects, and Criticality Analysis (FMECA).
- Data Integration: Clean and analyze telemetry, maintenance logs, and supply chain data using programming languages and tools like Python, SQL, Palantir Foundry.
- FRACAS Management: Support the Failure Reporting, Analysis, and Corrective Action System (FRACAS) to identify trends in component failures and improve product lifecycle management.
- Cross-Functional Collaboration: Partner with software engineering, logistics, and field operations to automate data collection and improve technical documentation.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.