Service Technology Engineering Intern - Graduate Level (Summer 2027)

JOB SUMMARY

Vertiv is seeking a Service Technology Research Intern to support and accelerate the development of next-generation service technologies for cooling and power systems used in high-performance computing and AI-driven data center environments.

This role is open to graduate students, including master's students, doctoral students, and PhD candidates pursuing advanced study in engineering, applied data science, computer science, digital systems, or a related technical field. The position is intended for candidates who can translate academic research, analysis, and technical problem solving into practical service concepts, pilots, and deployable service technologies.

The intern will work as a technical contributor and research partner to the Services Technology leadership team, helping evaluate emerging technologies and convert research opportunities into actionable service use cases.

KEY RESPONSIBILITIES

· Conduct applied research into emerging service technologies related to condition-based maintenance, digital services, IoT-enabled diagnostics, reliability engineering, and service analytics.

· Translate academic research, coursework, or thesis-related concepts into practical service use cases, pilots, proofs of concept, or technology recommendations.

· Evaluate algorithms, models, architectures, tools, or analytical methods that may improve service efficiency, asset reliability, field diagnostics, or maintenance decision-making.

· Support technology readiness assessments, maturity planning, and pilot planning for new service concepts.

· Collaborate with service, engineering, product, and regional teams to support pilot execution and collect technical feedback.

· Author technical documentation, internal research briefs, white papers, test summaries, and recommendations that can be used by service and engineering stakeholders.

· Provide recommendations on future research directions, partnership opportunities, and investment priorities for service technology development.

REQUIREMENTS

· Currently enrolled in a graduate degree program, including a master's degree, doctoral degree, or PhD program, in Engineering, Applied Sciences, Computer Science, Data Science, Reliability Engineering, Controls, Digital Systems, or a related technical discipline.

· Graduate students with research, thesis, capstone, laboratory, or applied project experience relevant to service technology are encouraged to apply.

· Interest or experience in predictive maintenance, data analytics, machine learning, IoT systems, controls, sensors, diagnostics, thermal systems, power systems, or reliability engineering.

· Ability to connect technical theory with applied engineering, service operations, field use cases, and business impact.

· Strong written and verbal communication skills, with the ability to summarize technical findings for both technical and non-technical audiences.

· Ability to work independently while collaborating with cross-functional teams in a professional business environment.

PREFERRED QUALIFICATIONS

· Experience using data analysis, simulation, modeling, programming, laboratory testing, or instrumentation tools to solve technical problems.

· Exposure to industrial equipment, data center infrastructure, HVAC/thermal systems, power systems, embedded systems, controls, or connected products.

· Demonstrated ability to develop research questions, evaluate technical alternatives, and communicate findings through reports, presentations, or prototypes.

· For doctoral or PhD candidates: experience translating advanced research into applied technology concepts is preferred but not required.

WHY JOIN VERTIV?

This role offers a practical opportunity for a graduate student to apply research and technical problem solving to mission-critical data center infrastructure challenges at global scale. The intern will contribute to Vertiv's long-term digital service strategy by helping identify, evaluate, and mature technologies that can improve serviceability, reliability, and customer outcomes.

 

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