RoboStruct Technologies builds intelligent robotics systems that improve accuracy, speed, and safety in manufacturing and logistics. It develops collaborative robots and AI-driven mechatronics platforms that integrate sensors, actuators, and control software to work with humans. The company operates in industrial automation and robotics engineering for businesses across sectors. Key technologies include AI, machine learning for perception and control, robotics hardware, and software integrations with factory systems. This approach supports scaling operations and making work safer and more efficient.
RoboStruct Technologies builds intelligent robotics systems that improve accuracy, speed, and safety in manufacturing and logistics. It develops collaborative robots and AI-driven mechatronics platforms that integrate sensors, actuators, and control software to work with humans. The company operates in industrial automation and robotics engineering for businesses across sectors. Key technologies include AI, machine learning for perception and control, robotics hardware, and software integrations with factory systems. This approach supports scaling operations and making work safer and more efficient.
Intern, Complex Systems Diagnostics and Prognostics Design, Summer 2026
Summary:
We are seeking a highly motivated and detail-oriented summer intern to join our Fleet Health Management and Remote Diagnostics team. As an intern you will contribute to the development of a unified framework for Vehicle and Fleet Health Management (VHM/FHM). It is a strategic initiative focused on predictive diagnostics and intelligent fault management across vehicle platforms. As well as other related duties under the mentorship of senior engineers.
Essential Duties & Responsibilities:
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Contribute to Lucid’s Fleet Health Management (FHM) and Prognostics and Health Management (PHM) initiatives.
Advance the development of a unified framework for monitoring and managing vehicle health across individual vehicles and entire fleets.
System Health Modeling: Developing models that represent the health of vehicle components, subsystems, and full systems using telemetry data, engineering design inputs, and software diagnostics.
Knowledge Base Development: Building a flexible and scalable diagnostic knowledge base that integrates vehicle architecture, hardware, and software—designed to support multiple trims and vehicle types.
AI/ML-Driven Fault Detection: Applying machine learning techniques to identify early signs of failure, isolate root causes, and recommend mitigation strategies before issues escalate.
Knowledge Graph & LLM Integration: Exploring the use of knowledge graphs and large language models to enhance fault reasoning, automate diagnostic logic generation, and improve explainability and scalability of health management systems.
Build a flexible and scalable knowledge base that integrates vehicle architecture, hardware, and software—designed to be applicable across multiple trims and vehicle types.
Work closely with technical specialists and system architects to translate engineering knowledge into actionable diagnostic & prognostic models.
Required Qualifications:
Strong understanding of AI/ML techniques in the domain of Prognostics and Health Management (PHM), with emphasis on early failure detection, fault isolation, and mitigation strategies.
Strong foundation in systems engineering or vehicle architecture.
Experience with data analysis and machine learning (especially time-series and anomaly detection).
Familiarity with Prognostics and Health Management (PHM) concepts.
Exposure to knowledge representation techniques such as knowledge graphs.
Proficiency in Python or similar programming languages with relevant AI/ML libraries.
Excellent written and verbal communication skills.
Ability to work independently and collaboratively in a team environment.
Field(s) of study: Electrical, Mechanical Engineering, or a related field.
Currently enrolled in a Master’s or PhD degree program at an accredited university.
Proof of enrollment in current or into the next program (MS, PhD).
Experience with vehicle telemetry systems or signal processing.
Familiarity with LLMs or generative AI frameworks.
Exposure to semantic modeling or ontology development.
Compensation:
The compensation for this role is $50.00–$70.00 / hr.
Who We Are:
We are an internationally recognized HR consultancy firm helping
candidates match with the potential roles by using an Artificial Intelligence System which is free of cost.
We are a global market leader who works
with several top-tier companies, tech startups, freelancers, industry professionals, and subject matter experts for projects, internships, and jobs.
Important:
The successful application submission for the above role(s) will be conditional to your profile evaluation by our Recruitment Specialists using the AI system. We can let you know better once you submit your resume.
