Test Intern – Hardware / Firmware
As a Test Intern, you will collaborate closely with engineers and industry experts to design, develop, and test hardware and firmware solutions that enhance industrial operations. This role offers hands-on experience, meaningful technical contributions, and broad exposure to how the business operates and delivers Connected Enterprise solutions to customers.
Internship Focus Areas
Hardware Test
Develop test requirements and execute hardware verification and validation plans
Perform board-level functional testing, EMC validation, and compliance testing with certification agencies (UL, ATEX, IECEx)
Support Functional Safety testing in accordance with IEC 61508 standards
Program, analyze, and troubleshoot electronic hardware prototypes
Contribute to product design documentation and detailed test reports
Firmware Test
Design and develop scripts to automate test procedures
Document and execute manual and automated test cases to verify product functionality
Generate and maintain test reports
Support lab audits and continuous improvement initiatives
Assist with building and commissioning test firmware and hardware platforms
Qualifications & Skills
Currently pursuing a bachelor’s or advanced degree in Electrical Engineering or a related field from an accredited institution
Basic programming experience in one or more of the following: C++, C#, Java, Python, JavaScript, or LabVIEW
Fundamental understanding of circuit theory, including microprocessors, digital logic, analog circuits, DC power conversion, and programmable devices (CPLDs, FPGAs)
Exposure to power electronics and/or motor systems
Experience using design capture tools and interpreting schematic diagrams
Familiarity with tools such as CAD software, Creo Parametric, ERP systems, 3D modeling tools, SAP, and MATLAB
Exposure to industrial automation environments, including PLCs or drive programming
Understanding or experience working within Agile development methodologies
Compensation
Hourly pay range: $22–$32, based on experience and qualifications
Application Process
We are an HR consultancy that uses a free AI-driven system to help candidates match with suitable roles. If you meet the eligibility criteria, we encourage you to apply. Once you submit your resume, our recruitment team will assess your profile, highlight your strengths, and help guide your career strategy.
If you want, I can also make this shorter, more technical, or more student-friendly depending on where you plan to post it.
You said:
Position Title: 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:
● 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 anPosition Title: 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:
● 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.d 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.
Rephrase it and make it a linkedin job description
ChatGPT said:
Here’s a clean, professional LinkedIn-style job description, rephrased for clarity, impact, and readability while keeping it attractive to graduate-level candidates:
Intern, Complex Systems Diagnostics & Prognostics Design (Summer 2026)
We are looking for a highly motivated and detail-oriented Summer Intern to join the Fleet Health Management and Remote Diagnostics team. In this role, you will support the development of a unified Vehicle and Fleet Health Management (VHM/FHM) framework—a strategic initiative focused on predictive diagnostics, intelligent fault management, and system-level health monitoring across vehicle platforms.
Working under the mentorship of senior engineers and system architects, you will gain hands-on experience applying AI/ML techniques, systems engineering principles, and advanced diagnostics methodologies to real-world automotive systems.
Key Responsibilities
Contribute to Fleet Health Management (FHM) and Prognostics and Health Management (PHM) initiatives
Support the development of a scalable, unified framework for monitoring vehicle health across individual vehicles and entire fleets
Develop system health models representing the condition of vehicle components, subsystems, and full systems using telemetry data, engineering inputs, and software diagnostics
Build and maintain a flexible diagnostic knowledge base integrating vehicle architecture, hardware, and software across multiple trims and vehicle platforms
Apply AI/ML techniques for early failure detection, fault isolation, root-cause analysis, and mitigation strategy recommendations
Explore knowledge graphs and large language models (LLMs) to enhance fault reasoning, automate diagnostic logic generation, and improve explainability and scalability
Collaborate with system architects and technical specialists to translate engineering knowledge into actionable diagnostic and prognostic models
Required Qualifications
Strong understanding of AI/ML techniques applied to Prognostics and Health Management (PHM)
Solid foundation in systems engineering or vehicle architecture
Experience with data analysis and machine learning, particularly time-series data and anomaly detection
Familiarity with PHM concepts and diagnostic methodologies
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 both independently and collaboratively in a team environment
Preferred Qualifications
Experience with vehicle telemetry systems or signal processing
Familiarity with LLMs or generative AI frameworks
Exposure to semantic modeling or ontology development
Education
Currently enrolled in a Master’s or PhD program in Electrical Engineering, Mechanical Engineering, or a related field
Proof of enrollment in a current or upcoming graduate program (MS or PhD)
Compensation
$50.00 – $70.00 per hour, based on qualifications and experience
About Us
We are an internationally recognized HR consultancy firm that helps candidates connect with top-tier companies, tech startups, and global organizations. Using our AI-driven recruitment system (free of cost), we evaluate candidate profiles to identify strong matches for internships, projects, and full-time roles worldwide.
