Artificial Intelligence for Flight Control Laws Internship

Job Description:

We are seeking a highly motivated Intern to support the development and deployment of an Integrated Knowledge and Reporting Platform. This role focuses on bridging the gap between manual engineering analysis and automated, AI-driven solutions. You will work at the intersection of data science, natural language processing, and real-time data integration to enhance operational efficiency and decision-making quality.
 

Key Responsibilities

• Knowledge Engineering: Load, structure, and integrate historical document databases and discussion records into a centralized AI environment.

• AI Development: Assist in building and tuning a conversational chatbot interface capable of "real-time analysis" and automated drafting.

• Data Integration: Connect and ingest live, time-based data streams for automated trend and root-cause analysis.

• Performance Optimization: Implement and test Retrieval-Augmented Generation (RAG) techniques to ensure high-quality outputs and minimize system errors.

• Risk & Security: Support the deployment of solutions within secure, compliant environments, focusing on data privacy and local hosting requirements.

Ideally, this is a 6-month program and it should start in July 2026 (date subject to flexibility).
 

Required Skills & Qualifications

Technical Skills

• Data Science & AI: Proficiency in Python and Large Language Models (LLMs). Familiarity with Retrieval-Augmented Generation (RAG) is highly desirable for failure justification tasks.

• Time-Series Analysis: Ability to process and interpret time-based engineering data to identify trends and root causes (e.g., distinguishing between turbulence and model reaction time).

• Cloud & DevOps: Familiarity with Google Cloud Platform (GCP) or local GPU on-premise environments for model deployment.

• Data Engineering: Skills in structuring unstructured data from historical documents into a searchable, machine-readable format.

Domain & Soft Skills

• Aerospace Awareness: Basic understanding of control laws to assist the development team in "domain support".

• Analytical Rigor: Ability to perform root cause analysis and validate AI-generated content against engineering standards.

• Communication: Capability to work within a multidisciplinary team (Data Scientists and Control Law Engineers) to translate technical failures into sophisticated draft paragraphs.

This job requires an awareness of any potential compliance risks and a commitment to act with integrity, as the foundation for the Company’s success, reputation and sustainable growth.

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